Despite the advances in information retrieval the search engines still result in imprecise or poor results, mainly due to the quality of the query being submitted. The query formulation to express their information need has always been challenging for the users. In this paper, we have proposed an interactive query expansion methodology using Concept-Based Directions Finder (CBDF). The approach ...

Community Question-Answering (cQA) platforms have become massive repositories of user-generated content. To a great extent, these archives have proven to be highly re-usable. For instance, web search engines profit from their best answers for enhancing user experience when resolving question-like queries. Hence, considerable research efforts have gone into trying to revitalize and retrieve past...

This paper analyses the efficiency of the EWC semantic relatedness measure in an ad-hoc retrieval task. This measure combines the Wikipedia-based Explicit Semantic Analysis (ESA) measure, the WordNet path measure and the mixed collocation index. EWC considers encyclopaedic, ontological, and collocational knowledge about terms. This advantage of EWC is a key factor to find precise terms for auto...

We present the UKP system which performed best in the Semantic Textual Similarity (STS) task at SemEval-2012 in two out of three metrics. It uses a simple log-linear regression model, trained on the training data, to combine multiple text similarity measures of varying complexity. These range from simple character and word n-grams and common subsequences to complex features such as Explicit Sem...

For our first participation to the CLEF CHiC Lab, we submitted runs to the multilingual ad-hoc and multilingual semantic enrichment tasks. Given the strong multilingual character of the evaluation corpus, the main objectives of the experiments were to test the efficiency of semantic topic expansion and consolidation based on Explicit Semantic Analysis (ESA) versions in different languages. Anot...

Laypeople (e.g., patients and their caregivers) usually use queries which describe a sign, symptom or condition to obtain relevant medical information on the Web. They can fail to find useful information for diagnosing or understanding their health conditions because the search results delivered by existing medical search engines do not fit the information needs of users. To deliver useful medi...

This paper reports on the participation of the LKD team in the English entity linking task at the TAC KBP 2013. We evaluated various modifications and combinations of the MostFrequent-Sense (MFS) based linking, the Entity Co-occurrence based linking (ECC), and the Explicit Semantic Analysis (ESA) based linking. We employed two our Wikipediabased NER systems, the Entityclassifier.eu and the Semi...

This paper describes the system used by the LIPN team in the Semantic Textual Similarity task at SemEval 2013. It uses a support vector regression model, combining different text similarity measures that constitute the features. These measures include simple distances like Levenshtein edit distance, cosine, Named Entities overlap and more complex distances like Explicit Semantic Analysis, WordN...

In this year’s Semantic Textual Similarity evaluation, we explore the contribution of models that provide soft similarity scores across spans of multiple words, over the previous year’s system. To this end, we explored the use of neural probabilistic language models and a TF-IDF weighted variant of Explicit Semantic Analysis. The neural language model systems used vector representations of indi...

Our aim is to find syntactic and semantic relationships and roles of words based on the analysis of corpora. We study three methods for analyzing words in contexts as potential methods for solving this task. The methods are latent semantic analysis, self-organizing map and independent component analysis. Latent semantic analysis is a simple method for automatic generation of concepts that are u...