In this paper we study the influence of semantics in the Text Categorization (TC) and Information Retrieval (IR) tasks. The K Nearest Neighbours (K-NN) method was used to perform the text categorization. The experimental results were obtained taking into account for a relevant term of a document its corresponding WordNet synset. For the IR task, three techniques were investigated: the direct us...

WordNet represents a cornerstone in the Computational Linguistics field, linking words to meanings (or senses) through a taxonomical representation of synsets, i.e., clusters of words with an equivalent meaning in a specific context often described by few definitions (or glosses) and examples. Most of the approaches to the Word Sense Disambiguation task fully rely on these short texts as a sour...

In the work reported here, we present three important related issues. 1. We present an effective method of construction of the Marathi WordNet (http://www. cfilt.iitb.ac.in/wordnet/webmwn/) using the Hindi WordNet (http://www.cfilt. iitb.ac.in/wordnet/webhwn/), both of which are being developed at IIT Bombay. Henceforth we will refer to them as MWN and HWN respectively. 2. The Synset identity i...

WordNets mostly deal with lexicalized expressions and lexical-semantic relations among them. Concepts are represented by sets of synonyms (synsets), which constitute the edges of the network. Each synset includes the lexicalized expressions that correspond to a given concept. This paper adduces evidences which support the claim that some concepts, expressed by a subtype of complex telic predica...

This paper presents a WordNet based approach to text summarization. The document to be summarized is used to extract a “relevant” sub-graph from the WordNet graph. Weights are assigned to each node of this sub-graph using a strategy similar to the Google Pageranking algorithm. These weights capture the relevance of the respective synsets with respect to the whole document. A matrix in which eac...

This paper presents an Extended WordNet based word sense disambiguation system using a major modification to the Lesk algorithm. The algorithm tries to disambiguate nouns, verbs and adjectives. The algorithm relies on the POS-sense tagged synset glosses provided by the Extended WordNet. The basic unit of disambiguation of our algorithm is the entire sentence under consideration. It takes a glob...

Morphing between face images that are expressing different emotions results in stimuli ambiguous terms of category membership. Within a categorical perception framework, the status these is questionable: they should either be uncategorizable as one parent or their ambiguity may mean categorized emotion other with low confidence. However, also unique signal emotional states distinct from based o...

Th~s paper presents an on-going project mtended to enhance WordNet molpholog~cally and semanttcally The mottvatmn for th~s work steams from the current hm~tat~ons of WordNet when used as a hngmst~c knowledge base We enwmon a software tool that automatically parses the conceptual defining glosses, attributing part-ofspeech tags and phrasal brackets The nouns, verbs, adjectives and adverbs from e...

In a manually built-up semantic net in which not the concept definitions automatically determine the position of the concepts in the net, but rather the links coded by the lexicographers, the formal properties of the encoded attributes and relations provide necessary but not sufficient conditions to support maintenance of internal consistency and avoidance of redundancy. According to our experi...

This study addresses the usage of different features to complement synset-based and bag-of-words representations texts in context using classical ML approaches for spam filtering (Ferrara, 2019). Despite existence a large number complementary features, order improve applicability this study, we have selected only those that can be computed regardless communication channel used distribute conten...