Mobile Search through Dynamic Mashups

Nowadays, mobile devices are the first choice for seeking information and content consumption on the Web. However, the overwhelming amount of available web resources, significantly affects the quality of the results returned by search systems. Traditionally, the web resource's retrieval is performed by using syntactic and/or semantic matches between the user query and content of the resources, leaving aside aspects such as: Goals and intentions that an end-user has when performing a query. This paper introduces a novel approach that allows to improve the mobile search user experience, delivering results according to his goals and intentions. This proposal is based on three main processes: i) To infer goals and intentions of end-users from their search query through a probabilistic generative model called LDA (Latent Dirichlet Allocation). ii) to discover resources based on inferred goals and intentions. And iii) to generate a dynamic mash up with the retrieved resources. We argue that the concept of mash up can contribute to improve the user experience in mobile search. Experiments show promising results in the user search experience in contrast to traditional approaches.