On the value of temporal information in information retrieval

ABSTRACT

Time is an important dimension of any information space and can be very useful in information retrieval. Current information retrieval systems and applications do not take advantage of all the time information available in the content of documents to provide better search results and user experience. In this paper we show some of the areas that can benefit from exploiting such temporal information.

REFERENCES

• 1: James Allan , Rahul Gupta , Vikas Khandelwal, Temporal summaries of new topics, Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval, p.10-18, September 2001, New Orleans, Louisiana, United States [doi>10.1145/383952.383954]
• 2: Omar Alonso , Michael Gertz, Clustering of search results using temporal attributes, Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval, August 06-11, 2006, Seattle, Washington, USA [doi>10.1145/1148170.1148273]
• 3: Omar Alonso, Ricardo Baeza-Yates, and Michael Gertz. Exploratory Search Using Timelines. In SIGCHI 2007 Workshop on Exploratory Search and HCI Workshop, 2007.
• 4: Google Timeline, http://www.google.com/experimental/
• 5: GUTime, http://complingone.georgetown.edu/~linguist
• 6: D. B. Koen , W. Bender, Time frames: temporal augmentation of the news, IBM Systems Journal, v.39 n.3-4, p.597-616, July 2000
• 7: Inderjeet Mani , James Pustejovsky , Beth Sundheim, Introduction to the special issue on temporal information processing, ACM Transactions on Asian Language Information Processing (TALIP), v.3 n.1, p.1-10, March 2004 [doi>10.1145/1017068.1017069]
• 8: Inderjeet Mani, James Pustejovsky, J., and Robert J. Gaizauskas R. (Eds.). The Language of Time. Oxford University Press, 2005.
• 9: Meredith Ringel, Edward Cutrell, Susan T. Dumais, Eric Horvitz. "Milestones in Time: The Value of Landmarks in Retrieving Information from Personal Stores". IFIP TC13 Intern. Conf. on Human-Computer Interaction, 184--191, 2003.
• 10: Frank Schilder , Christopher Habel, From temporal expressions to temporal information: semantic tagging of news messages, Proceedings of the workshop on Temporal and spatial information processing, p.1-8, July 07-07, 2001 [doi>10.3115/1118238.1118247]
• 11: Benyah Shaparenko, Rich Caruana, Johannes Gehrke, and Thorsten Joachims. "Identifying Temporal Patterns and Key Players in Document Collections". In Proc. of the IEEE ICDM Workshop on Temporal Data Mining: Algorithms, Theory and Applications (TDM-05), 165--174, 2005.
• 12: SIMILE Timeline toolkit, http://simile.mit.edu/timeline/
• 13: TimeML, Markup Language for Temporal and Event Expressions, http://www.timeml.org/
• 14: TimeWall, http://www.inxight.com/products/sdks/tw

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval

Additional Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.4 Knowledge Representation Formalisms and Methods
          Subjects: Temporal logic
  I.5 PATTERN RECOGNITION
      I.5.4 Applications
          Subjects: Text processing

General Terms:
Algorithms, Design, Theory