Hideki Kawai
ABSTRACT
In this paper, we propose an on-demand search engine called ChronoSeeker, which allows users to find past/future events based on their interest. Our goal is providing a search engine which can collect as many future/past events as possible relevant to user's query in obtaining various future scenarios considering both predictions and histories. Two technical issues are treated, (1) efficient search method for event information and (2) accurate filtering method for removing noises from search results. To search for event information effectively, our system expands a user query by some typical expressions related to event information such as year expressions, temporal modifiers and context terms. To remove noisy information, we selected five types of features for a machine learning technique to classify candidates into event information or not. Our experiment showed that filtering performance achieved an 85% F-measure, and that query expansion can collect dozens of times more CEs than those without expansion.
- R. Baeza-Yates. Searching the Future, ACM SIGIR Workshop MF/IR, 2005.Google Scholar
- P. Brun, H. Kawai, K. Kunieda, K. Yamada. ChronoSeeker: Future Opinion Extraction and Classification. The 2009 IEEE/WIC/ACM International Conference on Web Intelligence, 2009. Google ScholarDigital Library
- M. D. Choudhury, H. Ssundaram, A. John and D. D. Seligman. Can Blog Communication Dynamics be Correlated with Stock Market Activity?, Proceedings of HT2008, pp. 55--60, 2008. Google ScholarDigital Library
- D. Gruhl, R. V. Guha, R. Kumar, J. Novak, A. Tomkins. The Predictive Power of Online Chatter. Proceedings of SIGKDD2005, pp. 78--87, 2005. Google ScholarDigital Library
- S. Itaya, T. Konishi, R. Tanaka, S. Doi, K. Yamada. Experiments on Personal Opinion Expression and Consensus Building using "Future Chronicle". Second International Symposium on Universal Communication, 2008. Google ScholarDigital Library
- A. Jatowt, K. Kanazawa, S. Oyama, K. Tanaka. Supporting analysis of future-related information in news archives and the web. 9th ACM/IEEE-CS joint conference on Digital libraries, 2009. Google ScholarDigital Library
- S. Kim, H. Alani, W. Hall, P. H. Lewis, D. E. Millard, N. R. Shadbolt, M. J. Weal. Artequakt. Generating Tailored Biographies with Automatically Annotated Fragments from the Web, Semantic Authoring. Annotation and Knowledge Markup Workshop in the 15th European Conference on Artificial Intelligence, 2002.Google Scholar
- R. Kimura, S. Oyama, K. Tanaka. Automatic Collection of Personal Histories for Generating Who's Who from the Web. (in Japanese), DBSJ Letters, 5(2), 2006.Google Scholar
- Y. Liu, X. Huang, A. An and X. Yu. ARSA: a Sentimentaware Model for Predicting Sales Performance Using Blogs. Proceedings of SIGIR 2007, pp. 607--614, 2007. Google ScholarDigital Library
- I. Mani, J. Pustejovsky, B. Sundheim. Introduction to the special issue on temporal information processing. ACM Transactions on Asian Language Information Processing, 3(1):1--10, 2004. Google ScholarDigital Library
- G. Mishne, N. Glance. Predicting Movie Sales from Blogger Sentiment. Proceedings of the Spring Symposia on Computational Approaches to Analyzing Weblogs, 2006.Google Scholar
- M. Pasca, D. Lin, J. Bigham, A. Lifchits, A. Jain. Organizing and Searching the World Wide Web of Facts - Step One: the One-Million Fact Extraction Challenge. The 21st National Conference on Artificial Intelligence, 2006. Google ScholarDigital Library
- A. Pepe, J. Bollen. Between Conjecture and Memento:Shaping a Collective Emotional Perception of the Future. Proceedings of the AAAI 2008 Spring Symposium on Emotion, Personality and Social Behavior, 2008.Google Scholar
- A. Podelko. Multiple Dimensions of Performance Requirements. 33rd International Computer Measurement Group Conference, 2007.Google Scholar
- V. N. Vapnik. The Nature of Statistical Learning Theory. Springer, 1995. Google ScholarDigital Library
- J. Wolfers, E. Zitzewitz, Prediction Markets. Journal of Economic Perspectives, 18(2):107--126, 2004.Google ScholarCross Ref
- B. Wuthrich, D. Permunetilleke, S. Leung, V. Cho, J. Zhang, W. Lam. Daily Prediction of Major Stock Indices from textual WWW Data. Proceedings of SIGKDD1998, pp. 364--368, 1998.Google ScholarCross Ref
- Zona Research. The Need for Speed II. Zona Market Bulletin, Issue 05, 2001.Google Scholar
Index Terms
- ChronoSeeker: search engine for future and past events
Recommendations
The impact of images on user clicks in product search
MDMKDD '12: Proceedings of the Twelfth International Workshop on Multimedia Data MiningProduct search engine faces unique challenges that differ from web page search. The goal of a product search engine is to rank relevant items that the user may be interested in purchasing. Clicks provide a strong signal of a user's interest in an item. ...
The 2nd workshop on Vertical Search Relevance at WSDM 2015
WSDM '15: Proceedings of the Eighth ACM International Conference on Web Search and Data MiningAs the web information exponentially grows and the needs of users become more specific, traditional general web search engines are not able to perfectly satisfy the nowadays user requirement. Vertical search engines have emerged in various domains, ...
Online Exploration for Detecting Shifts in Fresh Intent
CIKM '14: Proceedings of the 23rd ACM International Conference on Conference on Information and Knowledge ManagementIn web search, recency ranking refers to the task of ranking documents while taking into account freshness as one of the criteria of their relevance. There are two approaches to recency ranking. One focuses on extending existing learning to rank ...
Comments