Abstract

Google is a tool for retrieving high-value information, but its growing adaptation of search results to commercial criteria, based on an alleged adaptation to user preferences of the links offered, presents some problems. Now it is neccessary to filter the information, to use operators or to modify the queries in order to obtain the desired results. Some tips are offered for information professionals who want to rebel against the false concept of relevance and find what we’re looking for.

Abstract

hough deep neural networks have been proving to be excellent tools to deliver state-of-the-art results, when data is scarce and the tackled tasks involve complex semantic inference, deep linguistic processing and traditional structure-based approaches, such as tree kernel methods, are an alternative solution. Community Question Answering is a research area that benefits from deep linguistic analysis to improve the experience of the community of forum users. In this paper, we present a UIMA framework to distribute the computation of cQA tasks over computer clusters such that traditional systems can scale to large datasets and deliver fast processing.