TF-IDF (term frequency-inverse document frequency) is one of the traditional text similarity calculation methods based on statistics. Because does not consider semantic information words, it cannot accurately reflect between texts, and enhanced distinguish documents poorly because extended vectors with similar terms aggravate curse dimensionality. Aiming at this problem, paper advances a hybrid...

Arabic Multiword Term are relevant strings of words in text documents. Once they are automatically extracted, they can be used to increase the performance of any text mining applications such as Categorisation, Clustering, Information Retrieval System, Machine Translation, and Summarization, etc. This paper introduces our proposed Multiword term extraction system based on the contextual informa...

phrases. The partial parser is motivated by an intuition (Abney, 1991): To acquire noun phrases from running texts is useful for many applications, such as word grouping, terminology indexing, etc. The reported literatures adopt pure probabilistic approach, or pure rule-based noun phrases grammar to tackle this problem. In this paper, we apply a probabilistic chunker to deciding the implicit bo...

We present an algorithm for bilingual word alignment that extends previous work by treating multi-word candidates on a par with single words, and combining some simple assumptions about the translation process to capture alignments for low frequency words. As most other alignment algorithms it uses cooccurrence statistics as a basis, but differs in the assumptions it makes about the translation...

17- Abtract — In the Persian language, an Ezafe construction is a linking element which joins the head of a phrase to its modifiers. The Ezafe in its simplest form is pronounced as –e, but generally not indicated in writing. Determining the position of an Ezafe is advantageous for disambiguating the boundary of the syntactic phrases which is a fundamental task in most natural language processi...