Query Answering in the Semantic Social Web: An Argumentation-Based Approach

MARIA VANINA MARTINEZ; SEBASTIAN GOTTIFREDI

Encyclopedia of Social Network Analysis and Mining 2014

Springer

Año: 2014; p. 1441 - 1455

The amount of information on the Web and the number of its human users have been growing exponentially in recent years. For many people, the Web has started to play a fundamental role as a means of providing and searching for information and services. The next revolution in Web search as one of the key technologies of the Web has just started with the incorporation of ideas from the Semantic Web, aiming at transforming currentWeb search into some form of semantic search and query answering on the Web, by adding meaning to Web contents and queries in the form of an underlying ontology.On the other hand, the Web has fostered the proliferation of web-based communities and on-line social networks. Social networking services (SNSs) allow Web users to create and maintain an online network of close friends or business associates for social and professional reasons. The  Social Web includes services such as Flickr, Facebook, Twitter, last.fm, among many other social and and business oriented sites. This web of social sites, containing huge amounts of data and collective knowledge, demands the need forinformation integration, dissemination, reuse, searchability and other more complex tasks such as querying and recommendation. The various and rich Semantic Web methodologies and tools seem to be the ideal platform to represent people and the objects that link them together in a social network. Furthermore, the use of standard representation formatsfacilitates the communication and linkage of data across different sites.The application of Semantic Web methodologies to the Social Web is leading to a Social Semantic Web, a network of interlinked and semantically rich knowledge. The focus of research in the Social Semantic Web currently aims to the interlinking of documents, data, and even applications created by the end users themselves as the result of various social interactions, modeled and represented using machine-readable formats.In light of this vision, we propose a framework for query answering on the Social Semantic Web. Similar in spirit to the recent initiative from Google, called The Knowledge Graph,we propose to leverage the complex knowledge base that emerges from the combination of social sites, networks, and applications, to allow a user to query and extract general information from it. In a sense, we envision this framework to be used as a combination of semantic search facilitator and a recommender system, exploiting the rich and vast knowledge base that we, as users of the Web, feed with constant information about ourselves and the world that surrounds us.