Using Query Profiles for Clarification

The following paper proposes a new kind of relevance feedback. It shows how so-called query profiles can be employed for disambiguation and clarification. Query profiles provide useful summarized previews on the retrieved answers to a given query. They outline ambiguity in the query and when combined with appropriate means of interactivity allow the user to easily adapt the final ranking. Statistical analysis of the profiles even enables the retrieval system to automatically suggest search restrictions or preferences. The paper shows a preliminary experimental study of the proposed feedback methods within the setting of TREC's interactive HARD track.

[1]  Nicholas J. Belkin,et al.  Interaction with Texts: Information Retrieval as Information-Seeking Behavior , 1993, Information Retrieval.

[2]  Gerard Salton,et al.  Improving retrieval performance by relevance feedback , 1997, J. Am. Soc. Inf. Sci..

[3]  Fabrizio Sebastiani Text Categorization , 2005, Encyclopedia of Database Technologies and Applications.

[4]  Elizabeth Bradley Analysis of time series , 2003 .

[5]  Wessel Kraaij,et al.  Variations on language modeling for information retrieval , 2005, SIGF.

[6]  Robert Godin,et al.  Design of a browsing interface for information retrieval , 1989, SIGIR '89.

[7]  W. Bruce Croft Combining Approaches to Information Retrieval , 2002 .

[8]  James Allan,et al.  HARD Track Overview in TREC 2003: High Accuracy Retrieval from Documents , 2003, TREC.

[9]  W. Bruce Croft Advances in Information Retrieval , 2000, The Information Retrieval Series.

[10]  A. Zanasi Text Mining and its Applications to Intelligence, CRM and Knowledge Management , 2007 .

[11]  Víctor Pàmies,et al.  Open Directory Project , 2003 .

[12]  Chris Chatfield,et al.  The Analysis of Time Series , 1990 .

[13]  James Allan,et al.  HARD Track Overview in TREC 2004 (Notebook) High Accuracy Retrieval from Documents , 2004 .

[14]  W. Bruce Croft Advances in Informational Retrieval: Recent Research from the Center for Intelligent Information Retrieval , 2000 .

[15]  Robin Burke,et al.  USING CONCEPT HIERARCHIES TO ENHANCE USER QUERIES IN WEB-BASED INFORMATION RETRIEVAL , 2003 .

[16]  Donna K. Harman,et al.  Relevance feedback revisited , 1992, SIGIR '92.

[17]  Tobun Dorbin Ng,et al.  Demonstration of hierarchical document clustering of digital library retrieval results , 2001, JCDL '01.

[18]  Djoerd Hiemstra,et al.  Conceptual Language Models for Context-Aware Text Retrieval , 2004, TREC.

[19]  Fernando Diaz,et al.  Using temporal profiles of queries for precision prediction , 2004, SIGIR '04.