Social Search

Social Search

social-search-line

How can we use data generated by users to provide recommendations?

Social search is a behavior of retrieving and searching on a social searching engine that mainly searches user-generated content such as news, videos and images related search queries on social media.

Our research in social search consists on automating some aspects of users’ interaction with the aim to improve and speed-up the results. We have proposed several query-routing mechanisms, and published a state-of-the art about the automation of social search.

Currently we are working on the applicability through NLP, to provide recommendations as a recommender system using data extracted from Twitter.

Related articles

These are some articles written by research members of Centre Easy

Applying short-term memory to social search agents

Year: 2015

Authors: A Trias i Mansilla, Sam Sethserey, Josep Lluís de la Rosa

Reference: Procedia Computer Science 68, 217-226  

Question Waves: A multicast query routing algorithm for social search

Year: 2013

Authors: Albert Trias i MansillaJosep Lluís de la Rosa i Esteva

Reference: Information Sciences, Volume 253, 20 December 2013, Pages 1–25

Survey of social search from the perspectives of the village paradigm and online social networks

Year: 2013

Authors: Albert Trias i MansillaJosep Lluís de la Rosa i Esteva

Reference: Journal of Information Science, October 2013 vol. 39 no. 5 688-707

Asknext: An agent protocol for social search

Year: 2012

Authors: Albert Trias i MansillaJosep Lluís de la Rosa i Esteva

Reference: Information Sciences, Volume 190, 1 May 2012, Pages 144–161

Social Presence Approach Within the Question and Answering eLearning Model: An Experiment with a Multi-Agent System

Year: 2012

Authors: C Avila, J Bacca, JL de la Rosa, S Baldiris, R Fabregat

Reference: Revista Respuestas 17 (1), 27-34 

Propagation of question waves by means of trust in a social network

Year: 2011

Authors: AT Mansilla, JL de la Rosa Esteva

Reference: Flexible Query Answering Systems, 186-197 

A negotiation-style recommender based on computational ecology in open negotiation environments

Year: 2011

Authors: JL de la Rosa, N Hormazábal, S Aciar, G Lopardo, A Trias, M Montaner

Reference: Industrial Electronics, IEEE Transactions on 58 (6), 2073-2085