Slides for the presentation of the paper entitled "Hierarchical Taxonomy Extraction By Mining Topical Query Sessions" in proceedeings of the 1st International Conference on Knowledge Discovery and Information Retrieval (KDIR) celebrated in Madeira in 2009
Axa Assurance Maroc - Insurer Innovation Award 2024
Hierarchical taxonomy extraction
1. KDIR09
International Conference On Knowledge
Hierachical taxonomy extraction
by mining topical query sessions
Dicovery and Information Retrieval 2009 Miguel Fernández Fernández and Daniel Gayo Avello
4. brittany spears
www.wikipedia.org
horse jumping
auto restoration
auto repair
classic car repair
car supplies
classic car batteries
vintageparts.com
“... a series of
interactions by the
low cost airlines user toward addressing
cheap flights a single information
easyjet.com need...”
Jansen et. al 2007
5. Unfortunatelly, not all Wang and Zhai 2008.
Mining term association patterns from
queries are equally effective search logs for effective query
reformulation.
6. Unfortunatelly, not all Wang and Zhai 2008.
Mining term association patterns from
queries are equally effective search logs for effective query
reformulation.
Mispeci
fication
different people use different
words to discribe the same thing!
7. Unfortunatelly, not all Wang and Zhai 2008.
Mining term association patterns from
queries are equally effective search logs for effective query
reformulation.
Mispeci
fication cification
Underspe
different people use different user has shallow knowledge about
words to discribe the same thing! what he is looking for
8. How can they be mitigated?
Und
e
n rspec
cifi catio ific
Mispe atio
n
19. hyponym |ˈhīpəˌnim|
a word of more specific meaning than a
general or superordinate term applicable to it.
20. hyponymy|ˈhīpəˌnim| |
hyponym | hīˈpänəmē
a word of more specific meaning than a
general or superordinate term applicable to it.
21. hyponymy|ˈhīpəˌnim| |
hyponym | hīˈpänəmē
a word of more specific meaning than a
general or superordinate term applicable to it.
Transitivity ➞ deductive power
22. hyponymy|ˈhīpəˌnim| |
hyponym | hīˈpänəmē
a word of more specific meaning than a
general or superordinate term applicable to it.
Transitivity ➞ deductive power
Socrates is mortal
23. hyponymy|ˈhīpəˌnim| |
hyponym | hīˈpänəmē
a word of more specific meaning than a
general or superordinate term applicable to it.
Transitivity ➞ deductive power
Socrates is mortal
Hyponym semantic equivalence (synsets)
24. hyponymy|ˈhīpəˌnim| |
hyponym | hīˈpänəmē
a word of more specific meaning than a
general or superordinate term applicable to it.
Socrates is mortal
Transitivity ➞ deductive power
Hyponym semantic equivalence (synsets)
Ferrari and Lamborghini are luxury cars
30. (d es ip te Hearst ‘92)
to ma atn in
Miller and FellBaun 1990
h ard
WordNet, an online Lexical Database
31. (d es ip te Hearst ‘92) langu
ma iatn n age specific
h ard to
Miller and FellBaun 1990
WordNet, an online Lexical Database
32. (d es ip te Hearst ‘92) langu
ma iatn n age specific
h to Miller and FellBaun 1990
ard absence of proper names,
WordNet, an online Lexical Database
jna daalargeot na,l slang
M . ’99
Gabrilovich & Markovitch ‘07
34. Automatically build hyponym taxonomies that
capture not only formal lexicon semantics, but
also relations between those terms actually
used by search engine users
Do it without needing additional sources of
information than the own query log
35. Automatic acquisition of hyponyms
from large text corpora (1992)
Caraballo, 1999. Automatic
construction of a hypernym-labeled
noun hierarchy from text.
Girju, Badulescu and Moldovan. 2003. Learning
Ma rti A. Hearst semantic constraints for the automatic discovery
of part-whole relations.
[...]
36. Baeza-Yates and Tiberi. 2007.
Extracting semantic relations
from query logs.
Shen et al. 2008. Mining web query
hierarchies from clickthrough data
Paşca ʻ07
Sekine and Suzuki ʼ07 Mika ʼ07
Schmitz ʼ06
Komachi and Suzuki ʼ08
37. Baeza-Yates and Tiberi. 2007.
Extracting semantic relations
from query logs.
a wi
asest oleut
whtho
ir es ugg
h y
Shen et al. 2008. Mining web query
queto s
ik ngrive ing
hierarchies from clickthrough data
Ta d now
Paşca ʻ07
Sekine and Suzuki ʼ07 Mika ʼ07
k w
Schmitz ʼ06
Komachi and Suzuki ʼ08
46. Daniel Gayo-Avello .2009. “A survey on session detection
methods in query logs and a proposal for future evaluation”
47. summer collection briefs 17:46:48
speedo summer collection 17:48:33
madonna get into the groove 17:55:47
madonna get into the groove 17:57:29
videogames cheats and codes 18:02:56
cheatsandcodes.com 18:10:27
madonna get into the groove 18:11:40
getintothegroovelyrics 18:12:27
Daniel Gayo-Avello .2009. “A survey on session detection
methods in query logs and a proposal for future evaluation”
48. summer collection briefs 17:46:48
speedo summer collection 17:48:33
madonna get into the groove 17:55:47
madonna get into the groove 17:57:29
madonna get into the groove 18:11:40
getintothegroovelyrics 18:12:27
videogames cheats and codes 18:02:56
cheatsandcodes.com 18:10:27
Daniel Gayo-Avello .2009. “A survey on session detection
methods in query logs and a proposal for future evaluation”
50. summer collection briefs 17:46:48
speedo summer collection 17:48:33
madonna get into the groove 17:55:47
madonna get into the groove 17:57:29
madonna get into the groove 18:11:40
getintothegroovelyrics 18:12:27
videogames cheats and codes 18:02:56
cheatsandcodes.com 18:10:27
51. summer collection briefs 17:46:48
speedo summer collection 17:48:33
madonna get into the groove 17:55:47
madonna get into the groove 17:57:29
madonna get into the groove 18:11:40
getintothegroovelyrics 18:12:27
videogames cheats and codes 18:02:56
cheatsandcodes.com 18:10:27
52. summer collection briefs 17:46:48
speedo summer collection 17:48:33
madonna get into the groove 17:55:47
madonna get into the groove 17:57:29
madonna get into the groove 18:11:40
getintothegroovelyrics 18:12:27
videogames cheats and codes 18:02:56
cheatsandcodes.com 18:10:27
Jim Jansen and Amanda Spink. 2008. Determining the
informational, navigational and transactional intent of
queries.
53. summer collection briefs 17:46:48
speedo summer collection 17:48:33
madonna get into the groove 17:55:47
madonna get into the groove 17:57:29
madonna get into the groove 18:11:40
getintothegroovelyrics 18:12:27
videogames cheats and codes 18:02:56
cheatsandcodes.com 18:10:27
Jim Jansen and Amanda Spink. 2008. Determining the
informational, navigational and transactional intent of
queries.
54. summer collection briefs 17:46:48
speedo summer collection 17:48:33
madonna get into the groove 17:55:47
madonna get into the groove 17:57:29
madonna get into the groove 18:11:40
getintothegroovelyrics 18:12:27
videogames cheats and codes 18:02:56
cheatsandcodes.com 18:10:27
55. summer collection briefs 17:46:48
speedo summer collection 17:48:33
madonna get into the groove 17:55:47
madonna get into the groove 17:57:29
madonna get into the groove 18:11:40
getintothegroovelyrics 18:12:27
videogames cheats and codes 18:02:56
cheatsandcodes.com 18:10:27
59. fish food
tropical fish food Terms added (trivial)
formula one pilots
Fernando Alonso Queries don’t share any term
60. fish food
tropical fish food Terms added (trivial)
opees don’t share any term
ut o Queri
f sc
formula one pilots
o
Fernando Alonso
61. fish food
tropical fish food Terms added (trivial)
opees don’t share any term
ut o Queri
f sc
formula one pilots
o
Fernando Alonso
speedo summer collection
summer collection briefs
Someremovrmsd added,
other te e
85. Work in progress
Machine Learning
specialization detection
Paolo Boldi et al. 2009.
From 'dango' to 'japanese cakes'
86. Work in progress
Machine Learning
specialization detection
Paolo Boldi et al. 2009.
From 'dango' to 'japanese cakes'
qi: Formula one pilots
qj: Fernando Alonso
87. Work in progress
Machine Learning Multi-word term
specialization detection identification
Paolo Boldi et al. 2009. Rosie Jones et al. 2006.
From 'dango' to 'japanese cakes' Generating query substitutions
qi: Formula one pilots
qj: Fernando Alonso
88. Work in progress
Machine Learning Multi-word term
specialization detection identification
Paolo Boldi et al. 2009. Rosie Jones et al. 2006.
From 'dango' to 'japanese cakes' Generating query substitutions
qi: Formula one pilots golden globe awards
qj: Fernando Alonso new york maps
97. KDIR09
International Conference On Knowledge
Hierachical taxonomy extraction
by mining topical query sessions
Dicovery and Information Retrieval 2009 Miguel Fernández Fernández and Daniel Gayo Avello