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Document Classification and Clustering for SMAI course
Document Classification and Clustering
Document Classification and Clustering
Ankur Shrivastava
Presentation of CSMR Algorithm
CSMR: A Scalable Algorithm for Text Clustering with Cosine Similarity and Map...
CSMR: A Scalable Algorithm for Text Clustering with Cosine Similarity and Map...
Victor Giannakouris
Document clustering for forensic analysis an approach for improving computer inspection
Document clustering for forensic analysis an approach for improving compute...
Document clustering for forensic analysis an approach for improving compute...
Madan Golla
Text clustering
Text clustering
KU Leuven
محاضرة ألقيتها ضمن برنامج السيمينار الذي نفذه قسم علوم الحاسوب وتكنولوجيا المعلومات في الكلية الجامعية للعلوم والتكنولوجيا عام 2012
Document clustering and classification
Document clustering and classification
Mahmoud Alfarra
Ir 08
Ir 08
Ir 08
Mohammed Romi
seminar presentation on web clustering engines!
web clustering engines
web clustering engines
Arun TR
Web clustering Engines are emerging trend in the field of data retrieval. They organize search results by topic, thus providing a complementary view to the flat ranked list returned by the standard search engines.
Web clustring engine
Web clustring engine
FACTS Computer Software L.L.C
Recomendados
Document Classification and Clustering for SMAI course
Document Classification and Clustering
Document Classification and Clustering
Ankur Shrivastava
Presentation of CSMR Algorithm
CSMR: A Scalable Algorithm for Text Clustering with Cosine Similarity and Map...
CSMR: A Scalable Algorithm for Text Clustering with Cosine Similarity and Map...
Victor Giannakouris
Document clustering for forensic analysis an approach for improving computer inspection
Document clustering for forensic analysis an approach for improving compute...
Document clustering for forensic analysis an approach for improving compute...
Madan Golla
Text clustering
Text clustering
KU Leuven
محاضرة ألقيتها ضمن برنامج السيمينار الذي نفذه قسم علوم الحاسوب وتكنولوجيا المعلومات في الكلية الجامعية للعلوم والتكنولوجيا عام 2012
Document clustering and classification
Document clustering and classification
Mahmoud Alfarra
Ir 08
Ir 08
Ir 08
Mohammed Romi
seminar presentation on web clustering engines!
web clustering engines
web clustering engines
Arun TR
Web clustering Engines are emerging trend in the field of data retrieval. They organize search results by topic, thus providing a complementary view to the flat ranked list returned by the standard search engines.
Web clustring engine
Web clustring engine
FACTS Computer Software L.L.C
Probabilistic models (part 1)
Probabilistic models (part 1)
KU Leuven
Tdm probabilistic models (part 2)
Tdm probabilistic models (part 2)
KU Leuven
Introduction to Text Mining:Textmining Retrieval And Clustering
Textmining Retrieval And Clustering
Textmining Retrieval And Clustering
guest0edcaf
Similarity Measurement Preliminary Results
Similarity Measurement Preliminary Results
xiaojuzheng
COLING 2014 読み会@首都大学東京で紹介した Single Document Keyphrase Extraction Using Label Information のスライドです。
Coling2014:Single Document Keyphrase Extraction Using Label Information
Coling2014:Single Document Keyphrase Extraction Using Label Information
Ryuchi Tachibana
About Query Evaluation and optimization in RDBMS
Query evaluation and optimization
Query evaluation and optimization
lavanya marichamy
Algorithm Name Detection in Research Papers in Computer Science.
IRE- Algorithm Name Detection in Research Papers
IRE- Algorithm Name Detection in Research Papers
SriTeja Allaparthi
Ghost
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Jhih-Ming Chen
From a code4lib online lightning talk in 04/2011.
Using SweetSpotSimilarity for Solr Fulltext Indexing
Using SweetSpotSimilarity for Solr Fulltext Indexing
Jay Luker
Overview of query evaluation
Overview of query evaluation
avniS
Data Mining-model based clustering
3.5 model based clustering
3.5 model based clustering
Krish_ver2
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sowfi
Extraction of Algorithm Name from Research Paper in computer Science domain
Algorithm Name Detection & Extraction
Algorithm Name Detection & Extraction
Deeksha thakur
Traditionally, machine learning based approaches to information retrieval have taken the form of supervised learning-to-rank models. Recently, other machine learning approaches—such as adversarial learning and reinforcement learning—have started to find interesting applications in retrieval systems. At Bing, we have been exploring some of these methods in the context of web search. In this talk, I will share couple of our recent work in this area that we presented at SIGIR 2018.
Adversarial and reinforcement learning-based approaches to information retrieval
Adversarial and reinforcement learning-based approaches to information retrieval
Bhaskar Mitra
Abstract— Text categorization is the process of identifying and assigning predefined class to which a document belongs. A wide variety of algorithms are currently available to perform the text categorization. Among them, K-Nearest Neighbor text classifier is the most commonly used one. It is used to test the degree of similarity between documents and k training data, thereby determining the category of test documents. In this paper, an improved K-Nearest Neighbor algorithm for text categorization is proposed. In this method, the text is categorized into different classes based on K-Nearest Neighbor algorithm and constrained one-pass clustering, which provides an effective strategy for categorizing the text. This improves the efficiency of K-Nearest Neighbor algorithm by generating the classification model. The text classification using K-Nearest Neighbor algorithm has a wide variety of text mining applications.
Text Categorization Using Improved K Nearest Neighbor Algorithm
Text Categorization Using Improved K Nearest Neighbor Algorithm
IJTET Journal
Hey friends, here is my "query tree" assignment. :-) I have searched a lot to get this master piece :p and I can guarantee you that this one gonna help you In Sha ALLAH more than any else document on the subject. Have a good day :-)
Query trees
Query trees
Shefa Idrees
Classification of common clustering algorithm and techniques, e.g., hierarchical clustering, distance measures, K-means, Squared error, SOFM, Clustering large databases.
05 Clustering in Data Mining
05 Clustering in Data Mining
Valerii Klymchuk
Data Mining: clustering and analysis
Data Mining: clustering and analysis
Data Mining: clustering and analysis
DataminingTools Inc
LSA Overview - Covers Singular Value Decomposition, Dimensionality Reduction, LSA in Information Retrieval
Latent Semanctic Analysis Auro Tripathy
Latent Semanctic Analysis Auro Tripathy
Auro Tripathy
Text document clustering and similarity detection is the major part of document management, where every document should be identified by its key terms and domain knowledge. Based on the similarity, the documents are grouped into clusters. For document similarity calculation there are several approaches were proposed in the existing system. But the existing system is either term based or pattern based. And those systems suffered from several problems. To make a revolution in this challenging environment, the proposed system presents an innovative model for document similarity by applying back propagation time stamp algorithm. It discovers patterns in text documents as higher level features and creates a network for fast grouping. It also detects the most appropriate patterns based on its weight and BPTT performs the document similarity measures. Using this approach, the document can be categorized easily. In order to perform the above, a new approach is used. This helps to reduce the training process problems. The above framework is named as BPTT. The BPTT has implemented and evaluated using dot net platform with different set of datasets.
Improved Text Mining for Bulk Data Using Deep Learning Approach
Improved Text Mining for Bulk Data Using Deep Learning Approach
IJCSIS Research Publications
Text Mining
Text categorization
Text categorization
KU Leuven
Clustering data into subsets is an important task for many data science applications. It is considered as one of the most important unsupervised learning technique. Keeping this in mind, we have come with a free webinar ‘Application of Cluster in Data Science using Real-life examples.’
Application of Clustering in Data Science using Real-life Examples
Application of Clustering in Data Science using Real-life Examples
Edureka!
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Probabilistic models (part 1)
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Introduction to Text Mining:Textmining Retrieval And Clustering
Textmining Retrieval And Clustering
Textmining Retrieval And Clustering
guest0edcaf
Similarity Measurement Preliminary Results
Similarity Measurement Preliminary Results
xiaojuzheng
COLING 2014 読み会@首都大学東京で紹介した Single Document Keyphrase Extraction Using Label Information のスライドです。
Coling2014:Single Document Keyphrase Extraction Using Label Information
Coling2014:Single Document Keyphrase Extraction Using Label Information
Ryuchi Tachibana
About Query Evaluation and optimization in RDBMS
Query evaluation and optimization
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lavanya marichamy
Algorithm Name Detection in Research Papers in Computer Science.
IRE- Algorithm Name Detection in Research Papers
IRE- Algorithm Name Detection in Research Papers
SriTeja Allaparthi
Ghost
Ghost
Jhih-Ming Chen
From a code4lib online lightning talk in 04/2011.
Using SweetSpotSimilarity for Solr Fulltext Indexing
Using SweetSpotSimilarity for Solr Fulltext Indexing
Jay Luker
Overview of query evaluation
Overview of query evaluation
avniS
Data Mining-model based clustering
3.5 model based clustering
3.5 model based clustering
Krish_ver2
QUERY PROCESSING
RDBMS
RDBMS
sowfi
Extraction of Algorithm Name from Research Paper in computer Science domain
Algorithm Name Detection & Extraction
Algorithm Name Detection & Extraction
Deeksha thakur
Traditionally, machine learning based approaches to information retrieval have taken the form of supervised learning-to-rank models. Recently, other machine learning approaches—such as adversarial learning and reinforcement learning—have started to find interesting applications in retrieval systems. At Bing, we have been exploring some of these methods in the context of web search. In this talk, I will share couple of our recent work in this area that we presented at SIGIR 2018.
Adversarial and reinforcement learning-based approaches to information retrieval
Adversarial and reinforcement learning-based approaches to information retrieval
Bhaskar Mitra
Abstract— Text categorization is the process of identifying and assigning predefined class to which a document belongs. A wide variety of algorithms are currently available to perform the text categorization. Among them, K-Nearest Neighbor text classifier is the most commonly used one. It is used to test the degree of similarity between documents and k training data, thereby determining the category of test documents. In this paper, an improved K-Nearest Neighbor algorithm for text categorization is proposed. In this method, the text is categorized into different classes based on K-Nearest Neighbor algorithm and constrained one-pass clustering, which provides an effective strategy for categorizing the text. This improves the efficiency of K-Nearest Neighbor algorithm by generating the classification model. The text classification using K-Nearest Neighbor algorithm has a wide variety of text mining applications.
Text Categorization Using Improved K Nearest Neighbor Algorithm
Text Categorization Using Improved K Nearest Neighbor Algorithm
IJTET Journal
Hey friends, here is my "query tree" assignment. :-) I have searched a lot to get this master piece :p and I can guarantee you that this one gonna help you In Sha ALLAH more than any else document on the subject. Have a good day :-)
Query trees
Query trees
Shefa Idrees
Classification of common clustering algorithm and techniques, e.g., hierarchical clustering, distance measures, K-means, Squared error, SOFM, Clustering large databases.
05 Clustering in Data Mining
05 Clustering in Data Mining
Valerii Klymchuk
Data Mining: clustering and analysis
Data Mining: clustering and analysis
Data Mining: clustering and analysis
DataminingTools Inc
LSA Overview - Covers Singular Value Decomposition, Dimensionality Reduction, LSA in Information Retrieval
Latent Semanctic Analysis Auro Tripathy
Latent Semanctic Analysis Auro Tripathy
Auro Tripathy
Text document clustering and similarity detection is the major part of document management, where every document should be identified by its key terms and domain knowledge. Based on the similarity, the documents are grouped into clusters. For document similarity calculation there are several approaches were proposed in the existing system. But the existing system is either term based or pattern based. And those systems suffered from several problems. To make a revolution in this challenging environment, the proposed system presents an innovative model for document similarity by applying back propagation time stamp algorithm. It discovers patterns in text documents as higher level features and creates a network for fast grouping. It also detects the most appropriate patterns based on its weight and BPTT performs the document similarity measures. Using this approach, the document can be categorized easily. In order to perform the above, a new approach is used. This helps to reduce the training process problems. The above framework is named as BPTT. The BPTT has implemented and evaluated using dot net platform with different set of datasets.
Improved Text Mining for Bulk Data Using Deep Learning Approach
Improved Text Mining for Bulk Data Using Deep Learning Approach
IJCSIS Research Publications
La actualidad más candente
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Probabilistic models (part 1)
Probabilistic models (part 1)
Tdm probabilistic models (part 2)
Tdm probabilistic models (part 2)
Textmining Retrieval And Clustering
Textmining Retrieval And Clustering
Similarity Measurement Preliminary Results
Similarity Measurement Preliminary Results
Coling2014:Single Document Keyphrase Extraction Using Label Information
Coling2014:Single Document Keyphrase Extraction Using Label Information
Query evaluation and optimization
Query evaluation and optimization
IRE- Algorithm Name Detection in Research Papers
IRE- Algorithm Name Detection in Research Papers
Ghost
Ghost
Using SweetSpotSimilarity for Solr Fulltext Indexing
Using SweetSpotSimilarity for Solr Fulltext Indexing
Overview of query evaluation
Overview of query evaluation
3.5 model based clustering
3.5 model based clustering
RDBMS
RDBMS
Algorithm Name Detection & Extraction
Algorithm Name Detection & Extraction
Adversarial and reinforcement learning-based approaches to information retrieval
Adversarial and reinforcement learning-based approaches to information retrieval
Text Categorization Using Improved K Nearest Neighbor Algorithm
Text Categorization Using Improved K Nearest Neighbor Algorithm
Query trees
Query trees
05 Clustering in Data Mining
05 Clustering in Data Mining
Data Mining: clustering and analysis
Data Mining: clustering and analysis
Latent Semanctic Analysis Auro Tripathy
Latent Semanctic Analysis Auro Tripathy
Improved Text Mining for Bulk Data Using Deep Learning Approach
Improved Text Mining for Bulk Data Using Deep Learning Approach
Destacado
Text Mining
Text categorization
Text categorization
KU Leuven
Clustering data into subsets is an important task for many data science applications. It is considered as one of the most important unsupervised learning technique. Keeping this in mind, we have come with a free webinar ‘Application of Cluster in Data Science using Real-life examples.’
Application of Clustering in Data Science using Real-life Examples
Application of Clustering in Data Science using Real-life Examples
Edureka!
Search Engines
Search Engines
butest
paper
Lime
Lime
Daniel LIAO
linear and logistic classification
C3.1.logistic intro
C3.1.logistic intro
Daniel LIAO
ML
C4.4
C4.4
Daniel LIAO
Atu media eval_sed2014
Atu media eval_sed2014
multimediaeval
ML
C4.1.1
C4.1.1
Daniel LIAO
UW-ML
C3.3.1
C3.3.1
Daniel LIAO
The Optimum Clustering Framework: Implementing the Cluster Hypothesis
The Optimum Clustering Framework: Implementing the Cluster Hypothesis
yaevents
© Yalemisew Mintesinot Abgaz
Amharic document clustering
Amharic document clustering
Guy De Pauw
ML
C4.5
C4.5
Daniel LIAO
Court Case Management System
Court Case Management System
Lahiru Manchanayake
Data Applied: Similarity
Data Applied: Similarity
Data Applied: Similarity
DataminingTools Inc
Oracle: Joins
Oracle: Joins
Oracle: Joins
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LISP: Type specifiers in lisp
LISP: Type specifiers in lisp
LISP: Type specifiers in lisp
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2010 Device Research Conference Presentation-Record Current Density Esaki Diodes
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Drc 2010 D.J.Pawlik
slrommel
Introduction to QSS Construction
Quantica Construction Search
Quantica Construction Search
QSSCONSTRUCT
World record GaAs Esaki reported on a Si substrate
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slrommel
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robyroby65
Destacado
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Text categorization
Text categorization
Application of Clustering in Data Science using Real-life Examples
Application of Clustering in Data Science using Real-life Examples
Search Engines
Search Engines
Lime
Lime
C3.1.logistic intro
C3.1.logistic intro
C4.4
C4.4
Atu media eval_sed2014
Atu media eval_sed2014
C4.1.1
C4.1.1
C3.3.1
C3.3.1
The Optimum Clustering Framework: Implementing the Cluster Hypothesis
The Optimum Clustering Framework: Implementing the Cluster Hypothesis
Amharic document clustering
Amharic document clustering
C4.5
C4.5
Court Case Management System
Court Case Management System
Data Applied: Similarity
Data Applied: Similarity
Oracle: Joins
Oracle: Joins
LISP: Type specifiers in lisp
LISP: Type specifiers in lisp
Drc 2010 D.J.Pawlik
Drc 2010 D.J.Pawlik
Quantica Construction Search
Quantica Construction Search
2008 IEDM presentation
2008 IEDM presentation
Presentazione oroblu
Presentazione oroblu
Similar a Textmining Retrieval And Clustering
TEXT CLUSTERING
TEXT CLUSTERING.doc
TEXT CLUSTERING.doc
naveenchaurasia
call for papers, research paper publishing, where to publish research paper, ...
call for papers, research paper publishing, where to publish research paper, ...
International Journal of Engineering Inventions www.ijeijournal.com
International Journal of Engineering and Science Invention (IJESI)
L0261075078
L0261075078
inventionjournals
International Journal of Engineering and Science Invention (IJESI)
L0261075078
L0261075078
inventionjournals
International Journal of Engineering and Science Invention (IJESI) is an international journal intended for professionals and researchers in all fields of computer science and electronics. IJESI publishes research articles and reviews within the whole field Engineering Science and Technology, new teaching methods, assessment, validation and the impact of new technologies and it will continue to provide information on the latest trends and developments in this ever-expanding subject. The publications of papers are selected through double peer reviewed to ensure originality, relevance, and readability. The articles published in our journal can be accessed online.
International Journal of Engineering and Science Invention (IJESI)
International Journal of Engineering and Science Invention (IJESI)
inventionjournals
International Journal of Engineering Research and Development is an international premier peer reviewed open access engineering and technology journal promoting the discovery, innovation, advancement and dissemination of basic and transitional knowledge in engineering, technology and related disciplines.
International Journal of Engineering Research and Development (IJERD)
International Journal of Engineering Research and Development (IJERD)
IJERD Editor
Electrical, Electronics and Computer Engineering, Information Engineering and Technology, Mechanical, Industrial and Manufacturing Engineering, Automation and Mechatronics Engineering, Material and Chemical Engineering, Civil and Architecture Engineering, Biotechnology and Bio Engineering, Environmental Engineering, Petroleum and Mining Engineering, Marine and Agriculture engineering, Aerospace Engineering.
E1062530
E1062530
IJERD Editor
CLUSTERING AND OUTLIER ANALYSIS
20IT501_DWDM_PPT_Unit_IV.ppt
20IT501_DWDM_PPT_Unit_IV.ppt
SamPrem3
Students can able to understand the different clustering methods in Data Mining concept
20IT501_DWDM_PPT_Unit_IV.ppt
20IT501_DWDM_PPT_Unit_IV.ppt
PalaniKumarR2
Bl24409420
Bl24409420
IJERA Editor
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Av33274282
Av33274282
IJERA Editor
IJERA (International journal of Engineering Research and Applications) is International online, ... peer reviewed journal. For more detail or submit your article, please visit www.ijera.com
Av33274282
Av33274282
IJERA Editor
Mathematical concept of clustering
Cluster
Cluster
guest1babda
The Volume of text resources have been increasing in digital libraries and internet. Organizing these text documents has become a practical need. For organizing great number of objects into small or minimum number of coherent groups automatically, Clustering technique is used. These documents are widely used for information retrieval and Natural Language processing tasks. Different Clustering algorithms require a metric for quantifying how dissimilar two given documents are. This difference is often measured by similarity measure such as Euclidean distance, Cosine similarity etc. The similarity measure process in text mining can be used to identify the suitable clustering algorithm for a specific problem. This survey discusses the existing works on text similarity by partitioning them into three significant approaches; String-based, Knowledge based and Corpus-based similarities.
A SURVEY ON SIMILARITY MEASURES IN TEXT MINING
A SURVEY ON SIMILARITY MEASURES IN TEXT MINING
mlaij
IOSR Journal of Computer Engineering (IOSRJCE)
Clustering Algorithm with a Novel Similarity Measure
Clustering Algorithm with a Novel Similarity Measure
IOSR Journals
International Journal of Modern Engineering Research (IJMER) is Peer reviewed, online Journal. It serves as an international archival forum of scholarly research related to engineering and science education. International Journal of Modern Engineering Research (IJMER) covers all the fields of engineering and science: Electrical Engineering, Mechanical Engineering, Civil Engineering, Chemical Engineering, Computer Engineering, Agricultural Engineering, Aerospace Engineering, Thermodynamics, Structural Engineering, Control Engineering, Robotics, Mechatronics, Fluid Mechanics, Nanotechnology, Simulators, Web-based Learning, Remote Laboratories, Engineering Design Methods, Education Research, Students' Satisfaction and Motivation, Global Projects, and Assessment…. And many more.
A Novel Multi- Viewpoint based Similarity Measure for Document Clustering
A Novel Multi- Viewpoint based Similarity Measure for Document Clustering
IJMER
FinalReportFoxMelle
FinalReportFoxMelle
Fridtjof Melle
This article will introduce some approaches for improving text categorization models by integrating previously imported ontologies. From the Reuters Corpus Volume I (RCV1) dataset, some categories very similar in content and related to telecommunications, Internet and computer areas were selected for models experiments. Several domain ontologies, covering these areas were built and integrated to categorization models for their improvements.
ONTOLOGY INTEGRATION APPROACHES AND ITS IMPACT ON TEXT CATEGORIZATION
ONTOLOGY INTEGRATION APPROACHES AND ITS IMPACT ON TEXT CATEGORIZATION
IJDKP
Barzilay & Lapata 2008 'Modeling Local Coherence: An Entity-Based Approach' presentation for Discourse Parsing and Language Technology seminar.
Barzilay & Lapata 2008 presentation
Barzilay & Lapata 2008 presentation
Richard Littauer
A novel clustering algorithm CSHARP is presented for the purpose of finding clusters of arbitrary shapes and arbitrary densities in high dimensional feature spaces. It can be considered as a variation of the Shared Nearest Neighbor algorithm (SNN), in which each sample data point votes for the points in its k-nearest neighborhood. Sets of points sharing a common mutual nearest neighbor are considered as dense regions/ blocks. These blocks are the seeds from which clusters may grow up. Therefore, CSHARP is not a point-to-point clustering algorithm. Rather, it is a block-to-block clustering technique. Much of its advantages come from these facts: Noise points and outliers correspond to blocks of small sizes, and homogeneous blocks highly overlap. This technique is not prone to merge clusters of different densities or different homogeneity. The algorithm has been applied to a variety of low and high dimensional data sets with superior results over existing techniques such as DBScan, K-means, Chameleon, Mitosis and Spectral Clustering. The quality of its results as well as its time complexity, rank it at the front of these techniques.
Clustering Using Shared Reference Points Algorithm Based On a Sound Data Model
Clustering Using Shared Reference Points Algorithm Based On a Sound Data Model
Waqas Tariq
Similar a Textmining Retrieval And Clustering
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TEXT CLUSTERING.doc
TEXT CLUSTERING.doc
call for papers, research paper publishing, where to publish research paper, ...
call for papers, research paper publishing, where to publish research paper, ...
L0261075078
L0261075078
L0261075078
L0261075078
International Journal of Engineering and Science Invention (IJESI)
International Journal of Engineering and Science Invention (IJESI)
International Journal of Engineering Research and Development (IJERD)
International Journal of Engineering Research and Development (IJERD)
E1062530
E1062530
20IT501_DWDM_PPT_Unit_IV.ppt
20IT501_DWDM_PPT_Unit_IV.ppt
20IT501_DWDM_PPT_Unit_IV.ppt
20IT501_DWDM_PPT_Unit_IV.ppt
Bl24409420
Bl24409420
Av33274282
Av33274282
Av33274282
Av33274282
Cluster
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A SURVEY ON SIMILARITY MEASURES IN TEXT MINING
A SURVEY ON SIMILARITY MEASURES IN TEXT MINING
Clustering Algorithm with a Novel Similarity Measure
Clustering Algorithm with a Novel Similarity Measure
A Novel Multi- Viewpoint based Similarity Measure for Document Clustering
A Novel Multi- Viewpoint based Similarity Measure for Document Clustering
FinalReportFoxMelle
FinalReportFoxMelle
ONTOLOGY INTEGRATION APPROACHES AND ITS IMPACT ON TEXT CATEGORIZATION
ONTOLOGY INTEGRATION APPROACHES AND ITS IMPACT ON TEXT CATEGORIZATION
Barzilay & Lapata 2008 presentation
Barzilay & Lapata 2008 presentation
Clustering Using Shared Reference Points Algorithm Based On a Sound Data Model
Clustering Using Shared Reference Points Algorithm Based On a Sound Data Model
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When you’re building (micro)services, you have lots of framework options. Spring Boot is no doubt a popular choice. But there’s more! Take Quarkus, a framework that’s considered the rising star for Kubernetes-native Java. It always depends on what's best for your situation, but how to choose the best solution if you're comparing 2 frameworks? Both Spring Boot and Quarkus have their positives and negatives. Let us compare the two by live coding a couple of common use cases in Spring Boot and Quarkus. After this talk, you’ll be ready to get started with Quarkus yourself, and know when to select Quarkus or Spring Boot.
Spring Boot vs Quarkus the ultimate battle - DevoxxUK
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Jago de Vreede
Uncertainty, Acting under uncertainty, Basic probability notation, Bayes’ Rule,
Artificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : Uncertainty
Khushali Kathiriya
ICT role in 21 century education. How to ICT help in education
presentation ICT roal in 21st century education
presentation ICT roal in 21st century education
jfdjdjcjdnsjd
We present an architecture of embedding models, vector databases, LLMs, and narrow ML for tracking global news narratives across a variety of countries/languages/news sources. As an example, we explore the real-time application of this architecture for tracking the news narrative surrounding the death of Russian opposition leader Alexei Navalny coming from Russian, French, and English sources.
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Zilliz
FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024
The Digital Insurer
JAM, the future of Polkadot.
Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Juan lago vázquez
The microservices honeymoon is over. When starting a new project or revamping a legacy monolith, teams started looking for alternatives to microservices. The Modular Monolith, or 'Modulith', is an architecture that reaps the benefits of (vertical) functional decoupling without the high costs associated with separate deployments. This talk will delve into the advantages and challenges of this progressive architecture, beginning with exploring the concept of a 'module', its internal structure, public API, and inter-module communication patterns. Supported by spring-modulith, the talk provides practical guidance on addressing the main challenges of a Modultith Architecture: finding and guarding module boundaries, data decoupling, and integration module-testing. You should not miss this talk if you are a software architect or tech lead seeking practical, scalable solutions. About the author With two decades of experience, Victor is a Java Champion working as a trainer for top companies in Europe. Five thousands developers in 120 companies attended his workshops, so he gets to debate every week the challenges that various projects struggle with. In return, Victor summarizes key points from these workshops in conference talks and online meetups for the European Software Crafters, the world’s largest developer community around architecture, refactoring, and testing. Discover how Victor can help you on victorrentea.ro : company training catalog, consultancy and YouTube playlists.
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Victor Rentea
The Good, the Bad and the Governed - Why is governance a dirty word? David O'Neill, Chief Operating Officer - APIContext Apidays New York 2024: The API Economy in the AI Era (April 30 & May 1, 2024) ------ Check out our conferences at https://www.apidays.global/ Do you want to sponsor or talk at one of our conferences? https://apidays.typeform.com/to/ILJeAaV8 Learn more on APIscene, the global media made by the community for the community: https://www.apiscene.io Explore the API ecosystem with the API Landscape: https://apilandscape.apiscene.io/
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
apidays
In this talk, we are going to cover the use-case of food image generation at Delivery Hero, its impact and the challenges. In particular, we will present our image scoring solution for filtering out inappropriate images and elaborate on the models we are using.
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
Zilliz
Tracing the root cause of a performance issue requires a lot of patience, experience, and focus. It’s so hard that we sometimes attempt to guess by trying out tentative fixes, but that usually results in frustration, messy code, and a considerable waste of time and money. This talk explains how to correctly zoom in on a performance bottleneck using three levels of profiling: distributed tracing, metrics, and method profiling. After we learn to read the JVM profiler output as a flame graph, we explore a series of bottlenecks typical for backend systems, like connection/thread pool starvation, invisible aspects, blocking code, hot CPU methods, lock contention, and Virtual Thread pinning, and we learn to trace them even if they occur in library code you are not familiar with. Attend this talk and prepare for the performance issues that will eventually hit any successful system. About authorWith two decades of experience, Victor is a Java Champion working as a trainer for top companies in Europe. Five thousands developers in 120 companies attended his workshops, so he gets to debate every week the challenges that various projects struggle with. In return, Victor summarizes key points from these workshops in conference talks and online meetups for the European Software Crafters, the world’s largest developer community around architecture, refactoring, and testing. Discover how Victor can help you on victorrentea.ro : company training catalog, consultancy and YouTube playlists.
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Victor Rentea
Explore how multimodal embeddings work with Milvus. We will see how you can explore a popular multimodal model - CLIP - on a popular dataset - CIFAR 10. You use CLIP to create the embeddings of the input data, Milvus to store the embeddings of the multimodal data (sometimes termed “multimodal embeddings”), and we will then explore the embeddings.
Exploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with Milvus
Zilliz
Three things you will take away from the session: • How to run an effective tenant-to-tenant migration • Best practices for before, during, and after migration • Tips for using migration as a springboard to prepare for Copilot in Microsoft 365 Main ideas: Migration Overview: The presentation covers the current reality of cross-tenant migrations, the triggers, phases, best practices, and benefits of a successful tenant migration Considerations: When considering a migration, it is important to consider the migration scope, performance, customization, flexibility, user-friendly interface, automation, monitoring, support, training, scalability, data integrity, data security, cost, and licensing structure Next Wave: The next wave of change includes the launch of Copilot, which requires businesses to be prepared for upcoming changes related to Copilot and the cloud, and to consolidate data and tighten governance ShareGate: ShareGate can help with pre-migration analysis, configurable migration tool, and automated, end-user driven collaborative governance
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
sammart93
MS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectors
Nanddeep Nachan
MINDCTI Revenue Release Quarter 1 2024
MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024
MIND CTI
Angeliki Cooney has spent over twenty years at the forefront of the life sciences industry, working out of Wynantskill, NY. She is highly regarded for her dedication to advancing the development and accessibility of innovative treatments for chronic diseases, rare disorders, and cancer. Her professional journey has centered on strategic consulting for biopharmaceutical companies, facilitating digital transformation, enhancing omnichannel engagement, and refining strategic commercial practices. Angeliki's innovative contributions include pioneering several software-as-a-service (SaaS) products for the life sciences sector, earning her three patents. As the Senior Vice President of Life Sciences at Avenga, Angeliki orchestrated the firm's strategic entry into the U.S. market. Avenga, a renowned digital engineering and consulting firm, partners with significant entities in the pharmaceutical and biotechnology fields. Her leadership was instrumental in expanding Avenga's client base and establishing its presence in the competitive U.S. market.
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
Angeliki Cooney
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Manulife - Insurer Transformation Award 2024
Manulife - Insurer Transformation Award 2024
Manulife - Insurer Transformation Award 2024
The Digital Insurer
Presentation from Melissa Klemke from her talk at Product Anonymous in April 2024
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
Product Anonymous
Join our latest Connector Corner webinar to discover how UiPath Integration Service revolutionizes API-centric automation in a 'Quote to Cash' process—and how that automation empowers businesses to accelerate revenue generation. A comprehensive demo will explore connecting systems, GenAI, and people, through powerful pre-built connectors designed to speed process cycle times. Speakers: James Dickson, Senior Software Engineer Charlie Greenberg, Host, Product Marketing Manager
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
DianaGray10
The action of the next cyber saga takes place in the mystical lands of the Asia-Pacific region, where the main characters began their digital activities in the middle of 2021 and qualitatively strengthened it in 2022. Corporate espionage, document theft, audio recordings, and data leaks from messaging platforms were all a matter of one day for Dark Pink. Their geographical focus may have started in the Asia-Pacific region, but their ambitions knew no bounds, targeting a European government ministry in a bold move to expand their portfolio. Their victim profile was as diverse as a UN meeting, targeting military organizations, government agencies, and even a religious organization. Because discrimination is not a fashionable agenda. In the world of cybercrime, they serve as a reminder that sometimes the most serious threats come in the most unassuming packages with a pink bow.
Cyberprint. Dark Pink Apt Group [EN].pdf
Cyberprint. Dark Pink Apt Group [EN].pdf
Overkill Security
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Spring Boot vs Quarkus the ultimate battle - DevoxxUK
Spring Boot vs Quarkus the ultimate battle - DevoxxUK
Artificial Intelligence Chap.5 : Uncertainty
Artificial Intelligence Chap.5 : Uncertainty
presentation ICT roal in 21st century education
presentation ICT roal in 21st century education
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
Emergent Methods: Multi-lingual narrative tracking in the news - real-time ex...
FWD Group - Insurer Innovation Award 2024
FWD Group - Insurer Innovation Award 2024
Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Polkadot JAM Slides - Token2049 - By Dr. Gavin Wood
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Modular Monolith - a Practical Alternative to Microservices @ Devoxx UK 2024
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
Apidays New York 2024 - The Good, the Bad and the Governed by David O'Neill, ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
"I see eyes in my soup": How Delivery Hero implemented the safety system for ...
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Finding Java's Hidden Performance Traps @ DevoxxUK 2024
Exploring Multimodal Embeddings with Milvus
Exploring Multimodal Embeddings with Milvus
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
MS Copilot expands with MS Graph connectors
MS Copilot expands with MS Graph connectors
MINDCTI Revenue Release Quarter One 2024
MINDCTI Revenue Release Quarter One 2024
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
Biography Of Angeliki Cooney | Senior Vice President Life Sciences | Albany, ...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
+971581248768>> SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHA...
Manulife - Insurer Transformation Award 2024
Manulife - Insurer Transformation Award 2024
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
ProductAnonymous-April2024-WinProductDiscovery-MelissaKlemke
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Connector Corner: Accelerate revenue generation using UiPath API-centric busi...
Cyberprint. Dark Pink Apt Group [EN].pdf
Cyberprint. Dark Pink Apt Group [EN].pdf
Textmining Retrieval And Clustering
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