theories of semantic fields are the most valuable topics of semantics in linguistic researches. this concept refers to the set of words which are the subset of a general meaning connected through special relations. in fact, semantics is the summary of words’ relations with each other. therefore, this study aims to investigate semantic fields in nahj al-fasaha, to explain relations among words i...

This paper describes our participation in the TEL@CLEF task of the CLEF 2009 adhoc track. The task is to retrieve items from various multilingual collections of library catalog records, which are relevant to a user’s query. Two different strategies are employed: (i) the Cross-Language Explicit Semantic Analysis, CL-ESA, where the library catalog records and the queries are represented in a mult...

We propose a similarity measure between sentences which combines a knowledge-based measure, that is a lighter version of ESA (Explicit Semantic Analysis), and a distributional measure, Rouge.We used this hybrid measure with two French domain-orientated corpora collected from the Web and we compared its similarity scores to those of human judges. In both domains, ESA and Rouge perform better whe...

This paper explores how to automatically generate cross-language links between resources in large document collections. The paper presents new methods for Cross-Lingual Link Discovery (CLLD) based on Explicit Semantic Analysis (ESA). The methods are applicable to any multilingual document collection. In this report, we present their comparative study on the Wikipedia corpus and provide new insi...

Dataless text classification [Chang et al., 2008] is a classification paradigm which maps documents into a given label space without requiring any annotated training data. This paper explores a crosslingual variant of this paradigm, where documents in multiple languages are classified into an English label space. We use CLESA (cross-lingual explicit semantic analysis) to embed both foreign lang...

Distributional semantic models (DSMs) are semantic models which are based on the statistical analysis of co-occurrences of words in large corpora. DSMs can be used in a wide spectrum of semantic applications including semantic search, question answering, paraphrase detection, word sense disambiguation, among others. The ability to automatically harvest meaning from unstructured heterogeneous da...

A content-based recommender system suggests items similar to those previously liked by a user, therefore the recommendation process consists of matching up the features stored in a user profile with those of a content object (item). Usually a content-based user profile stores keywords that are more meaningful for that specific user. Common-sense knowledge could positively enrich that profile an...

Manually labeling documents for training a text classifier is expensive and time-consuming. Moreover, a classifier trained on labeled documents may suffer from overfitting and adaptability problems. Dataless text classification (DLTC) has been proposed as a solution to these problems, since it does not require labeled documents. Previous research in DLTC has used explicit semantic analysis of W...

As a low-cost ressource that is up-to-date, Wikipedia recently gains attention as a means to provide cross-language brigding for information retrieval. Contradictory to a previous study, we show that standard Latent Dirichlet Allocation (LDA) can extract cross-language information that is valuable for IR by simply normalizing the training data. Furthermore, we show that LDA and Explicit Semanti...