Relationship extraction

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A relationship extraction task requires the detection and classification of semantic relationship mentions within a set of artifacts, typically from text or XML documents. The task is very similar to that of information extraction (IE), but IE additionally requires the removal of repeated relations (disambiguation) and generally refers to the extraction of many different relationships.

Applications[edit]

Application domains where relationship extraction is useful include gene-disease relationships,[1] protein-protein interaction[2] etc.

Approaches[edit]

One approach to this problem involves the use of domain ontologies.[3][4] Another approach involves visual detection of meaningful relationships in parametric values of objects listed on a data table that shift positions as the table is permuted automatically as controlled by the software user. The poor coverage, rarity and development cost related to structured resources such as semantic lexicons (e.g. WordNet, UMLS) and domain ontologies (e.g. the Gene Ontology) has given rise to new approaches based on broad, dynamic background knowledge on the Web. For instance, the ARCHILES technique[5] uses only Wikipedia and search engine page count for acquiring coarse-grained relations to construct lightweight ontologies.

The relationships can be represented using a variety of formalisms/languages. One such representation language for data on the Web is RDF.

See also[edit]

References[edit]

  1. ^ Hong-Woo Chun, Yoshimasa Tsuruoka, Jin-Dong Kim, Rie Shiba, Naoki Nagata, Teruyoshi Hishiki, Jun-ichi Tsujii (2006). "Pacific Symposium on Biocomputing".  |chapter= ignored (help)
  2. ^ Minlie Huang and Xiaoyan Zhu and Yu Hao and Donald G. Payan and Kunbin Qu and Ming Li (2004). "Bioinformatics" 20 (18). pp. 3604–3612. doi:10.1093/bioinformatics/bth451.  |chapter= ignored (help)
  3. ^ T.C.Rindflesch and L.Tanabe and J.N.Weinstein and L.Hunter (2000). "Proc. Pacific Symposium on Biocomputing". pp. 514–525.  |chapter= ignored (help)
  4. ^ C. Ramakrishnan and K. J. Kochut and A. P. Sheth (2006). "Proc. International Semantic Web Conference". pp. 583–596.  |chapter= ignored (help)
  5. ^ W. Wong and W. Liu and M. Bennamoun (2009). "Proc. 13th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD)". doi:10.1007/978-3-642-01307-2_26.  |chapter= ignored (help)