The present study focuses on the lexical meanings of prepositions rather than on the thematic meanings because it is intended for use in an English-Bengali machine translation (MT) system, where the meaning of a lexical unit must be preserved in the target language, even though it may take a different syntactic form in the source and target languages. Bengali is the fifth language in the world ...

The rise of social media such as blogs and social networks has fueled interest in sentiment analysis. With the proliferation of reviews, ratings, recommendations and other forms of online expression, online opinion has turned into a kind of virtual currency for businesses looking to market their products, identify new opportunities and manage their reputations, therefore many are now looking to...

This paper reports the process of developing WordNet Affect lists in Bengali from the affect wordlists already available in English. It is organized in six basic emotions such as anger, disgust, fear, joy, sadness and surprise. Emotion or affect words of the six lists are updated using equivalent synsets of the SentiWordNet by keeping their parts-of-speech information unchanged. Another updatin...

This task was meant to compare the results of two different retrieval techniques: the first one was based on the words found in documents and query texts; the second one was based on the senses (concepts) obtained by disambiguating the words in documents and queries. The underlying goal was to come up with a more precise knowledge about the possible improvements brought by word sense disambigua...

Samāsa or compounds are a regular feature of Indian Languages. They are also found in other languages like German, Italian, French, Russian, Spanish, etc. Compound word is constructed from two or more words to form a single word. The meaning of this word is derived from each of the individual words of the compound. To develop a system to generate, identify and interpret compounds, is an importa...

This paper introduces a recently initiated project that focuses on building a lexical resource for Modern Standard Arabic based on the widely used Princeton WordNet for English (Fellbaum, 1998). Our aim is to develop a linguistic resource with a deep formal semantic foundation in order to capture the richness of Arabic as described in Elkateb (2005). Arabic WordNet is being constructed followin...

Current state-of-the-art Word Sense Disambiguation (WSD) algorithms are mostly supervised and use the P (Sense|Word) statistic for annotation. This P (Sense|Word) statistic is obtained after training the model on an annotated corpus. The performance of WSD algorithms do not match the efficiency and quality of human annotation. It is therefore important to know the role of the contextual clues i...

With faster connection speed, Internet users are now making social network a huge reservoir of texts, images and video clips (GIF). Sentiment analysis for such online platform can be used to predict political elections, evaluates economic indicators and so on. However, GIF sentiment analysis is quite challenging, not only because it hinges on spatio-temporal visual contentabstraction, but also ...

The importance of describing regular polysemy in a lexicon has often been outlined, especially in the field of natural language processing (for a good overview of this issue, see (Ravin and Leacock, 2000)). Unfortunately, no existing broad-coverage semantic lexicon has been built following this relatively recent advice. And since producing a broad coverage semantic lexicon is a very time-consum...

In this paper we present the results of three years of experiments about automatic acquisition of domain specific terminology from corpora. We present an analysis of the potentiality and limitations of the Term Categorization approach to lexical acquisition, and we propose a novel methodology to approach the task, consisting on applying Latent Semantic Kernels to estimate term similarity. We fi...