Query expansion using local and global document analysis
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Extracting significant time varying features from text
Proceedings of the eighth international conference on Information and knowledge management
Automatic generation of overview timelines
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
First story detection in TDT is hard
Proceedings of the ninth international conference on Information and knowledge management
The Design and Implementation of a Part of Speech Tagger for English
The Design and Implementation of a Part of Speech Tagger for English
Nymble: a high-performance learning name-finder
ANLC '97 Proceedings of the fifth conference on Applied natural language processing
Capturing term dependencies using a language model based on sentence trees
Proceedings of the eleventh international conference on Information and knowledge management
Flexible intrinsic evaluation of hierarchical clustering for TDT
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
Simple Semantics in Topic Detection and Tracking
Information Retrieval
Robust techniques for organizing and retrieving spoken documents
EURASIP Journal on Applied Signal Processing
Relevance models for topic detection and tracking
HLT '02 Proceedings of the second international conference on Human Language Technology Research
Discovering event episodes from news corpora: a temporal-based approach
Proceedings of the 11th International Conference on Electronic Commerce
Temporal feature modification for retrospective categorization
FeatureEng '05 Proceedings of the ACL Workshop on Feature Engineering for Machine Learning in Natural Language Processing
Cross-language linking of news stories on the web using interlingual topic modelling
Proceedings of the 2nd ACM workshop on Social web search and mining
New event detection and topic tracking in Turkish
Journal of the American Society for Information Science and Technology
Topic detection and tracking with spatio-temporal evidence
ECIR'03 Proceedings of the 25th European conference on IR research
Recommendation in Internet forums and blogs
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
User comments for news recommendation in forum-based social media
Information Sciences: an International Journal
Story link detection based on event words
CICLing'11 Proceedings of the 12th international conference on Computational linguistics and intelligent text processing - Volume Part II
The Study of Content Security for Mobile Internet
Wireless Personal Communications: An International Journal
Representations for multi-document event clustering
Data Mining and Knowledge Discovery
| Hi-index | 0.00 |
This chapter presents the system used by the Center for Intelligent Information Retrieval (CIIR) at the University of Massachusetts for its participation in four of the five TDT tasks: tracking, detection, first story detection, and story link detection. For each task, we discuss the parameter setting approach that we used and the results of our system on the test data.For the task of link detection, we look more carefully at score normalization across different languages and media types. We find that we can improve results noticeably though not substantially by normalizing scores differently depending upon the source language. We also consider smoothing the vocabulary in stories using a "query expansion" technique from Information Retrieval to add additional words from the corpus to each story. This results in substantial improvements.In addition, we use TDT evaluation approaches to show that the tracking performance that sites are achieving is what is expected from Information Retrieval technology. We further show that any first story detection system based on a tracking approach is unlikely to be sufficiently accurate for most purposes. Finally, we present an overview of an automatic timeline generation system that we developed using TDT data.