This paper describes our experiments on Textual Entailment in the context of the Third Pascal Recognising Textual Entailment (RTE-3) Evaluation Challenge. Our system uses a Machine Learning approach with Support Vector Machines and AdaBoost to deal with the RTE challenge. We perform a lexical, syntactic, and semantic analysis of the entailment pairs . From this information we compute a set of s...

This paper shows a Recognizing Textual Entailment System, and a sub-system that address the Textual Entailment Search Task. This system employs a Support Vector Machine classifier with a set of 32 features, which includes lexical and semantic similarity for both two-way and three-way classification tasks. Additionally, we show an approach to dealing with the problem of searching entailment in a...

This paper describes a novel framework for using scenario knowledge in opendomain Question Answering (Q/A) applications that uses a state-of-the-art textual entailment system (Hickl et al., 2006b) in order to discover textual information relevant to the set of topics associated with a scenario description. An intrinsic and an extrinsic evaluation of this method is presented in the context of an...

The expansion in volume of information organized according to a structure in multiple applications introduces a new equivocal in multimedia retrieval in semi-structured documents. We study in this paper the impact of introduce a structural context on multimedia retrieval in XML document thus we present a indexing model which combines textual and structural information. We propose a geometric me...

In the general context of Knowledge Discovery, speciic techniques , called Text Mining techniques, are necessary to extract information from unstructured textual data. The extracted information can then be used for the classiication of the content of large textual bases. In this paper, we present two examples of information that can be automatically extracted from text collections: probabilisti...

Recent studies have found that people interpret emoji characters inconsistently, creating significant potential for miscommunication. However, this research examined emoji in isolation, without consideration of any surrounding text. Prior work has hypothesized that examining emoji in their natural textual contexts would substantially reduce the observed potential for miscommunication. To invest...

In modern applications, spatial objects are often annotated with textual descriptions, and users are offered the opportunity to formulate spatio-textual queries. The result set of such a query consists of spatio-textual objects ranked according to their distance from a desired location and to their textual relevance to the query. In this context, a challenging problem is how to select a set of ...

Data warehousing and On-Line Analytical Processing (OLAP) are essential elements to decision support. In the case of textual data, decision support requires new tools, mainly textual aggregation functions, for better and faster high level analysis and decision making. Such tools will provide textual measures to users who wish to analyse documents online. In this paper, we propose a new aggregat...