SIGDOC '86 Proceedings of the 5th annual international conference on Systems documentation
Automatic Topic Identification Using Ontology Hierarchy
CICLing '01 Proceedings of the Second International Conference on Computational Linguistics and Intelligent Text Processing
TopCat: Data Mining for Topic Identification in a Text Corpus
IEEE Transactions on Knowledge and Data Engineering
Identifying Document Topics Using the Wikipedia Category Network
WI '06 Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence
TF-IDF uncovered: a study of theories and probabilities
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Linking Documents to Encyclopedic Knowledge
IEEE Intelligent Systems
Using encyclopedic knowledge for automatic topic identification
CoNLL '09 Proceedings of the Thirteenth Conference on Computational Natural Language Learning
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
Topic identification using Wikipedia graph centrality
NAACL-Short '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers
DBpedia: a nucleus for a web of open data
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
Artificial intelligence
Entity classification by bag of Wikipedia articles
PIKM '10 Proceedings of the 3rd workshop on Ph.D. students in information and knowledge management
Concept-Based Information Retrieval Using Explicit Semantic Analysis
ACM Transactions on Information Systems (TOIS)
Ranking in context-aware recommender systems
Proceedings of the 20th international conference companion on World wide web
Personalized web search with user geographic and temporal preferences
APWeb'11 Proceedings of the 13th Asia-Pacific web conference on Web technologies and applications
Hi-index | 12.05 |
The increasing amount of Web-based tasks is currently requiring personalization strategies to improve the user experience. However, building user profiles is a hard task, since users do not usually give explicit information about their interests. Therefore, interests must be mined implicitly from electronic sources, such as chat and discussion forums. In this work, we present a novel method for topic detection from online informal conversations. Our approach combines: (i) Wikipedia, an extensive source of knowledge, (ii) a concept association strategy, and (iii) a variety of text-mining techniques, such as POS tagging and named entities recognition. We performed a comparative evaluation procedure for searching the optimal combination of techniques, achieving encouraging results.