This paper puts forward a two layers computing method to calculate semantic similarity of Chinese word. Firstly, using Latent Dirichlet Allocation (LDA) subject model to generate subject spatial domain. Then mapping word into topic space and forming topic distribution which is used to calculate semantic similarity of word(the first layer computing). Finally, using semantic dictionary"HowNet" to...

Semantic Textual Similarity is the task of finding the degree of similarity between a pair of sentences through semantics extraction. This is motivated by the fact that syntactically diverse sentences often convey the same meaning. This paper describes the approach that was used in the *SEM Shared Task 2013. The approach combines semantic, syntactic and lexical similarity measures for finding s...

Computing the semantic similarity between words is one of the key challenges in many language-based applications. Previous work tends to use the contextual information of words to disclose the degree of their similarity. In this paper, we consider the relationships between words in local contexts as well as latent topic information of words to propose a new distributed representation of words f...

a bilingual corpus is considered as a very important knowledge source and an inevitable requirement for many natural language processing (nlp) applications in which two languages are involved. for some languages such as persian, lack of such resources is much more significant. several applications, including statistical and example-based machine translation needs bilingual corpora, in which lar...

In this paper we introduce a new clustering algorithm for event detection in newspaper articles, which has two main features. Firstly, it makes use of the temporal references extracted from the document texts to define the document similarity function. Secondly, the algorithm works hierarchically. In the first level, documents with a high temporal-semantic similarity are grouped into individual...

The focus of this paper is the calculation of similarity between two concepts from an ontology for a Human-Like Interaction system. In order to facilitate this calculation, a similarity function is proposed based on five dimensions (sort, compositional, essential, restrictive and descriptive) constituting the structure of ontological knowledge. The paper includes a proposal for computing a simi...

Computing the semantic similarity between words is one of the key tasks in many language-based applications. Recent work has focused on using contextual clues for semantic similarity computation. In this paper, we propose a method to the measure semantic similarity between words using plain text contents. It takes into account information attributes (local) and topic information (global) of wor...

We present in this paper SEMILAR, the SEMantic simILARity toolkit. SEMILAR implements a number of algorithms for assessing the semantic similarity between two texts. It is available as a Java library and as a Java standalone ap-plication offering GUI-based access to the implemented semantic similarity methods. Furthermore, it offers facilities for manual se-mantic similarity annotation by exper...

Semantic Similarity relates to computing the similarity between conceptually similar but not necessarily lexically similar terms. Typically, semantic similarity is computed by mapping terms to an ontology and by examining their relationships in that ontology. We investigate approaches to computing the semantic similarity between natural language terms (using WordNet as the underlying reference ...

In this paper, we propose an algebraic similarity measure σBS (BS stands for BitSim) for assigning semantic similarity score to concept definitions in ALCH+ an expressive fragment of Description Logics (DL). We define an algebraic interpretation function, IB, that maps a concept-definition to a unique string (ωB) (called bit-code) over an alphabet ∑ B of 11 symbols belonging to LB the language ...