Authors:
Gianluca Moro
;
Roberto Pasolini
and
Claudio Sartori
Affiliation:
University of Bologna, Italy
Keyword(s):
Information Retrieval, Personalized Search, Query Expansion, Local Files, Search Engine.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Knowledge Discovery and Information Retrieval
;
Knowledge-Based Systems
;
Mining Text and Semi-Structured Data
;
Symbolic Systems
;
User Profiling and Recommender Systems
Abstract:
Users of Web search engines generally express information needs with short and ambiguous queries, leading to irrelevant results. Personalized search methods improve users’ experience by automatically reformulating queries before sending them to the search engine or rearranging received results, according to their specific interests. A user profile is often built from previous queries, clicked results or in general from the user’s browsing history; different topics must be distinguished in order to obtain an accurate profile. It is quite common that a set of user files, locally stored in sub-directory, are organized by the user into a coherent taxonomy corresponding to own topics of interest, but only a few methods leverage on this potentially useful source of knowledge. We propose a novel method where a user profile is built from those files, specifically considering their consistent arrangement in directories. A bag of keywords is extracted for each directory from text documents wit
hin it. We can infer the topic of each query and expand it by adding the corresponding keywords, in order to obtain a more targeted formulation. Experiments are carried out using benchmark data through a repeatable systematic process, in order to evaluate objectively how much our method can improve relevance of query results when applied upon a third-party search engine.
(More)