Similarity Assessment through blocking and affordance assignment in Textual CBR

TL;DR

This paper introduces a method for assessing similarity between web pages by extracting affordances based on user information needs, using case-based representations to improve retrieval relevance.

Contribution

It proposes a novel approach to assign affordances to web texts and utilize them for more effective document retrieval in specific domains.

Findings

Promising results in the tourism domain

Effective extraction and assignment of affordances

Improved relevance in web page retrieval

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.