Hippocampus: answering memory queries using transactive search

Michele Catasta, Alberto Tonon, Djellel Eddine Difallah, Gianluca Demartini, Karl Aberer, Philippe Cudré-Mauroux

Abstract: Memory queries denote queries where the user is trying to recall from his/her past personal experiences. Neither Web search nor structured queries can effectively answer this type of queries, even when supported by Human Computation solutions. In this paper, we propose a new approach to answer memory queries that we call Transactive Search: The user-requested memory is reconstructed from a group of people by exchanging pieces of personal memories in order to reassemble the overall memory, which is stored in a distributed fashion among members of the group. We experimentally compare our proposed approach against a set of advanced search techniques including the use of Machine Learning methods over the Web of Data, online Social Networks, and Human Computation techniques. Experimental results show that Transactive Search significantly outperforms the effectiveness of existing search approaches for memory queries.