Information filtering based on wiki index database

TL;DR

This paper introduces a profile-based information filtering method utilizing a Wikipedia index database to classify texts into user-specific topics, enhancing filtering accuracy for emails and news.

Contribution

It presents a novel approach that automatically generates user profiles and topic-specific Wikipedia subcorpora for improved information filtering.

Findings

Effective classification of texts into user interests

Successful application to Russian and Simple English Wikipedia

Demonstrated potential for personalized information filtering

Abstract

In this paper we present a profile-based approach to information filtering by an analysis of the content of text documents. The Wikipedia index database is created and used to automatically generate the user profile from the user document collection. The problem-oriented Wikipedia subcorpora are created (using knowledge extracted from the user profile) for each topic of user interests. The index databases of these subcorpora are applied to filtering information flow (e.g., mails, news). Thus, the analyzed texts are classified into several topics explicitly presented in the user profile. The paper concentrates on the indexing part of the approach. The architecture of an application implementing the Wikipedia indexing is described. The indexing method is evaluated using the Russian and Simple English Wikipedia.