Boletín Noviembre 2011

In recent years, studies have been dedicated mainly in the analysis, of crashes in real-world related to large-scale software systems. A crash in terms of computing can be termed as a computer program such as a software application that stops functioning properly. Software crash is a serious problem in production environment. When crash happens, the crash report with the stack trace of software at time of crash is sent to the developer team. Software development team may receive hundreds of stack traces from all deployment sites and many stack traces may be due to same problem. If the developer starts analyzing each trace, it may take a longer duration of time and redundancy many happen in terms of two developers fixing the same problem. This motivates us to present the solution to analyze the stack traces and find the important functions responsible for crash and rank them, so that development resources can be optimized. In this paper we have proposed the solution to solve the problem by developing Software CrashLocator.

Dictionary Based Approach to Sentiment Analysis - A Review

INFOGAIN PUBLICATION

Due to the fast growth of World Wide Web the online communication has increased. In recent times the communication focus has shifted to social networking. In order to enhance the text methods of communication such as tweets, blogs and chats, it is necessary to examine the emotion of user by studying the input text. Online reviews are posted by customers for the products and services on offer at a website portal. This has provided impetus to substantial growth of online purchasing making opinion analysis a vital factor for business development. To analyze such text and reviews sentiment analysis is used. Sentiment analysis is a sub domain of Natural Language Processing which acquires writer’s feelings about several products which are placed on the internet through various comments or posts. It is used to find the opinion or response of the user. Opinion may be positive, negative or neutral. In this paper a review on sentiment analysis is done and the challenges and issues involved in the process are discussed. The approaches to sentiment analysis using dictionaries such as SenticNet, SentiFul, SentiWordNet, and WordNet are studied. Dictionary-based approaches are efficient over a domain of study. Although a generalized dictionary like WordNet may be used, the accuracy of the classifier get affected due to issues like negation, synonyms, sarcasm, etc. w

Real Cost of TravelTim_Browne

Portafolio de computacion gabriela morocho 2 do a

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