English

Similarity Assessment through blocking and affordance assignment in Textual CBR

Information Retrieval 2013-01-07 v1 Artificial Intelligence

Abstract

It has been conceived that children learn new objects through their affordances, that is, the actions that can be taken on them. We suggest that web pages also have affordances defined in terms of the users' information need they meet. An assumption of the proposed approach is that different parts of a text may not be equally important / relevant to a given query. Judgment on the relevance of a web document requires, therefore, a thorough look into its parts, rather than treating it as a monolithic content. We propose a method to extract and assign affordances to texts and then use these affordances to retrieve the corresponding web pages. The overall approach presented in the paper relies on case-based representations that bridge the queries to the affordances of web documents. We tested our method on the tourism domain and the results are promising.

Keywords

Cite

@article{arxiv.1301.0701,
  title  = {Similarity Assessment through blocking and affordance assignment in Textual CBR},
  author = {R. Rajendra Prasath and Pinar Öztürk},
  journal= {arXiv preprint arXiv:1301.0701},
  year   = {2013}
}

Comments

10 pages, 3 figures, WebCBR 2010, Alessandria, Italy

R2 v1 2026-06-21T23:03:55.884Z