Semantic refinement for Web information retrieval

Abstract

As the Web has become one of the biggest repository of knowledge easily accessible for everyone, information retrieval has stopped to be an exclusive field of information sciences specialists, and it has become a field related with any person. Although users do not have to know information retrieval techniques, the proposal of this work is to improve query results by using a "specialist" that implements these techniques. For this, a semantic refiner is proposed. This refiner acts as a specialist in information sciences and prepares, using linguistic resources, an appropriate search strategy that represents the user's information need. The semantic refinement consists on three steps. First, it guides the user for sense disambiguation of the words submitted by him. Then, it allows the user to select concepts hierarchically related to reduce the amount of documents to retrieve. Finally, it expands semantically concepts to increase the amount of documents to be retrieved. A prototype is implemented using WordNet as linguistic resource, and experimental results are analyzed.