Children represent an increasing part of web users. One of the key problems that hamper their search experience is their limited vocabulary, their difficulty to use the right keywords, and the inappropriateness of general-purpose query suggestions. In this work we propose a method that utilizes tags from social media to suggest queries related to children topics. Concretely we propose a simple ...

Collaborative tagging systems have recently emerged as one of the most popular tools for Web search users to find their desired information. Indeed, the informal social classification structure in these systems, also known as folksonomy, provides a convenient way to annotate resources by allowing users to use any keyword or tag that they find relevant. In turn, the flat and non-hierarchical str...

Jointly with the release of RDF in 1999 as recommendation of the W3C, the natural problem of querying RDF data was raised. Since then, several designs and implementations of RDF query languages have been proposed (see [9] and [7] for detailed comparisons of RDF query languages). In 2004, the RDF Data Access Working Group released a first public working draft of a query language for RDF, called ...

Nearest Neighbor (NN) searching is a challenging problem in data management and has been widely studied in data mining, pattern recognition and computational geometry. The goal of NN searching is efficiently reporting the nearest data to a given object as a query. In most of the studies both the data and query are assumed to be precise, however, due to the real applications of NN searching, suc...

We describe a novel approach for cross-domain recommendation for research collaboration. We first constructed a large Neo4j graph database representing authors, their expertise, current collaborations, and general biomedical knowledge. This information comes from MEDLINE and from semantic relations extracted with SemRep. Then, by using an extended literature-based discovery paradigm, implemente...

This work presents a method to perform a location recommendation based on multiple criteria even when there is noise in the coordinates. More specifically, the skyline query is adapted to handle this noise by modeling the errors of geo-referenced points with an appropriate probability distribution and modifying the traditional dominance criterion used by that technique. The method is applied to...

In this paper we describe our effort on TREC Contextual Suggestion Track. We present a recommendation system that built upon ElasticSearch along with a machine learning re-ranking model. We utilize real world users’ opinion as well as other information to build user profiles. With profile information, we then construct customized ElasticSearch queries to search on various fields. After that, a ...

We investigate robust decision-making under utility uncertainty, using the maximin criterion, which optimizes utility for the worst case setting. We show how it is possible to efficiently compute the maximin optimal recommendation in face of utility uncertainty, even in large configuration spaces. We then introduce a new decision criterion, setwise maximin utility (SMMU), for constructing optim...

Online communities have become vital places for Web 2.0 users to share knowledge and experiences. Recently, finding expertise user in community has become an important research issue. This paper proposes a novel cascaded model for expert recommendation using aggregated knowledge extracted from enormous contents and social network features. Vector space model is used to compute the relevance of ...

the present article begins with an articulation of the significance and relation of ‘query and response’ with both dialogue and its semantic perimeters and discloses the sources of rumi’s thinking about this issue. after this taking a comparative stance, this article briefly explores the background and the significance of query and response, dialogue and dialectic as they relate to both ontolog...