Through this project, we will explore Semantic Textual Similarity a shared task in Sem Eval 2012. The problem involves comparing a pair of sentences for semantic equivalence, reporting the equivalence on a scale of 0 5 with 0 meaning no equivalence and 5 meaning semantically equivalent. This task is more challenging than determining if the two sentences are paraphrases (a simple yes/no answer),...

In recent years, semantic similarity measure has a great interest in Semantic Web and Natural Language Processing (NLP). Several similarity measures have been developed, being given the existence of a structured knowledge representation offered by ontologies and corpus which enable semantic interpretation of terms. Semantic similarity measures compute the similarity between concepts/terms inclu...

In this paper I argue that semantic similarity is not the only factor which motivates polysemy patterns cross-linguistically; I also show that these other factors (markedness, distinguishability, etc) may give rise to polysemies which are problematic for established semantic maps. Only when these other interfering factors, both functional and structural, are featured out, does a semantic networ...

This paper investigates measures of semantic similarity between conversations from an axiomatic perspective. We abstract away from real conversations, representing them as sequences of formulas, equipped with a notion of semantic interpretation that maps them into a different space. An example we use to illustrate our approach is the language of propositional logic with its classical semantics....

There are at least two kinds of similarity. Relational similarity is correspondence between relations, in contrast with attributional similarity, which is correspondence between attributes. When two words have a high degree of attributional similarity, we call them synonyms. When two pairs of words have a high degree of relational similarity, we say that their relations are analogous. For examp...

Evaluating semantic similarity of concepts is a problem that has been extensively investigated in the literature in different areas, such as artificial intelligence, cognitive science, databases and software engineering. Semantic similarity relates to computing the similarity between conceptually similar but not necessarily lexically similar terms. Currently, it is growing in importance in diff...

One of thechallenges in Latent Semantic Analysis (LSA) is deciding which corpus is best for a speci c̄ application.Imp ortant factors of LSA in°uence the generation of high quality LSA space including the size of the corpus, the weight (local or global) functions, number of dimensions to keep, etc. These factors are often di±cult to determine and as a result hard to control for. In this paper, w...

The standard representation of text documents as bags of words suffers from well known limitations, mostly due to its inability to exploit semantic similarity between terms. Attempts to incorporate some notion of term similarity include latent semantic indexing [8], the use of semantic networks [9], and probabilistic methods [5]. In this paper we propose two methods for inferring such similarit...

Determining semantic similarity between academic documents is crucial to many tasks such as plagiarism detection, automatic technical survey and semantic search. Current studies mostly focus on semantic similarity between concepts, sentences and short text fragments. However, document-level semantic matching is still based on statistical information in surface level, neglecting article structur...