Four-Valued Knowledge Augmentation for Structured Document Retrieval

Structured documents are composed of objects with a content and a logical structure. The effective retrieval of structured documents requires models that provide for a content-based retrieval of objects that takes into account their logical structure, so that the relevance of an object is not solely based on its content, but also on the logical structure among objects. This paper proposes a formal model for representing structured documents where the content of an object is viewed as the knowledge contained in that object, and the logical structure among objects is capture by a process of knowledge augmentation: the knowledge contained in an object is augmented with that of its structurally related objects. The knowledge augmentation process takes into account the fact that knowledge can be incomplete and become inconsistent.

[1]  Ian A. Macleod,et al.  Storage and retrieval of structured documents , 1990, Inf. Process. Manag..

[2]  Mounia Lalmas,et al.  Intelligent Retrieval of Hypermedia Documents , 2003, Intelligent Exploration of the Web.

[3]  James P. Callan,et al.  Passage-level evidence in document retrieval , 1994, SIGIR '94.

[4]  Jean-Pierre Chevallet,et al.  Toward a Structured Information Retrieval System on the Web: Automatic Structure Extraction of Web Pages , 2001, WebDyn@ICDT.

[5]  Norbert Fuhr,et al.  DOLORES: a system for logic-based retrieval of multimedia objects , 1998, SIGIR '98.

[6]  Norbert Fuhr,et al.  Retrieval of complex objects using a four-valued logic , 1996, SIGIR '96.

[7]  Forbes J. Burkowski Retrieval activities in a database consisting of heterogeneous collections of structured text , 1992, SIGIR '92.

[8]  Yves Chiaramella,et al.  Browsing and Querying: Two Complementary Approaches for Multimedia Information Retrieval , 1997, Hypertext, Information Retrieval, Multimedia.

[9]  Ross Wilkinson,et al.  Effective retrieval of structured documents , 1994, SIGIR '94.

[10]  M. de Rijke,et al.  Modal Logic , 2001, Cambridge Tracts in Theoretical Computer Science.

[11]  Gloria Bordogna,et al.  Flexible Querying of Structured Documents , 2000, FQAS.

[12]  Ricardo A. Baeza-Yates,et al.  A language for queries on structure and contents of textual databases , 1995, SIGIR '95.

[13]  Sung-Hyon Myaeng,et al.  A flexible model for retrieval of SGML documents , 1998, SIGIR '98.

[14]  Nicholas Kushmerick,et al.  Expressive retrieval from XML documents , 2001, SIGIR '01.

[15]  Ronald Fagin,et al.  Reasoning about knowledge , 1995 .

[16]  James Allan,et al.  Approaches to passage retrieval in full text information systems , 1993, SIGIR.

[17]  Norbert Fuhr,et al.  XIRQL: a query language for information retrieval in XML documents , 2001, SIGIR '01.

[18]  Evangelos Kotsakis,et al.  Structured information retrieval in XML documents , 2002, SAC '02.

[19]  Christoph Baumgarten,et al.  A probabilistic model for distributed information retrieval , 1997, Annual International ACM SIGIR Conference on Research and Development in Information Retrieval.

[20]  E. Frisse Mark,et al.  Searching for information in a hypertext medical handbook , 1988 .

[21]  Norbert Fuhr,et al.  Probabilistic Models in Information Retrieval , 1992, Comput. J..

[22]  Mounia Lalmas,et al.  A Dempster-Shafer indexing for the focused retrieval of a hierarchically structured document space: Implementation and experiments on a web museum collection , 2000, RIAO.

[23]  Mounia Lalmas,et al.  Dempster-Shafer's theory of evidence applied to structured documents: modelling uncertainty , 1997, SIGIR '97.

[24]  Guido Moerkotte,et al.  Querying documents in object databases , 1997, International Journal on Digital Libraries.

[25]  Nuel D. Belnap,et al.  A Useful Four-Valued Logic , 1977 .