An Ontology Based Personalizing Search Measure with the Protection of Original Engine Integrity
IR techniques are widely used to locate surfers’ interesting information resource on the Web. Every IR engine has its immanent advantage, while user’s retrieval hobby is also diverse. Thus, to satisfy individual, personalizing search becomes more and more popular. But, regardless of familiar environment for users, exist personalizing search measures just present a mixed result list from different engines. The combination destroys the integrity of original IR engine and pilot user to a strange interface. Aim to overcome the outstanding shortcoming, this paper presents an Ontology based personalizing search measure, which builds user profile and offers not a rigid combination result but the most appropriate engine with respect to query, so that the original engine integrity is protected. Some primary experiments illustrate that the measure is feasible and valuable.
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