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During the last decade the amount of scientific information available on-line increased at an unprecedented rate and this situation is unlikely to change. As a consequence, nowadays researchers are overwhelmed by an enormous and continuously growing number of publications to consider when they perform research activities like the exploration of advances in specific topics, peer reviewing, writing...
A context-aware approach based on machine learning and lexical analysis identifies ambiguous terms and stores them in contextualized sentiment lexicons, which ground the terms to concepts corresponding to their polarity.
A lexical resource is the central repository of data for all language processing applications. It contains information for human consumption as well as computer programs. A significant increase in the use of lexical databases has led WordNet to become one of the most widely used lexical information source for Natural Languages Processing (NLP) applications. This paper presents a methodology of constructing...
In this paper, a survey of researches on the application of natural language processing (NLP) in internet public opinion monitor (IPOM) was proposed. Key NLP technologies used in all stages of IPOM were introduced in detail. Two main difficulties that IPOM faces were also addressed. They are the problem of semantic understanding and the problem of sentiment analysis.
Multiword expressions (MWEs) are important for practical applications, such as machine translation (henceforth, MT), multilingual information retrieval, data mining and other natural language processing. A method of combining similarity measure and statistical tool is proposed for automatically extracting English MWEs from the corpus of Chinese government white papers and work reports from 1991 to...
In this paper, we propose a novel information retrieval approach based on the pragmatic information for Chinese patents. At present, patent retrieval is becoming more and more important. Not only because patents are always can an important resource in all kinds of field, but patent retrieval save a great deal of time and funds for corporations and researchers. However, with available methods the precision...
Machine translation, a part of computational Linguistics, belongs to Natural Language Processing (NLP) and is a hot issue in the computational society. Gap between the linguist and the computer programmer, gives birth to so many problems like lexical ambiguity, syntactic and structural ambiguity, polysemy, induction, discourses, anaphoric ambiguity and different shade of meanings. Mostly English-to-Urdu...
Pursuing on the analysis of product reviews, an unsupervised product features categorization method is proposed. Morphemes as smallest linguistic meaningful unit are induced in measuring the intra relationship among product features instead of words. Opinion words around product features are chosen to represent the inter relationship among product features instead of full context information. The...
Word sense disambiguation is an opened issue in the text mining and natural language processing for some time. Automatic acquisition of all distinct senses for polysemy words is still a big problem in the computer science. This paper discusses an approach to generate related words for an input word in some context. The context is used for the filtering of the related words for their distinct sense...
Cross-document coreference resolution plays an import part in the filed of natural language processing (NLP). It captures the ability of gathering documents for information about a certain entity. Most previous algorithms identify the underlying entity of a given document depending on the original text, which is unreliable if the original text contains multiple parts of different themes. In this paper,...
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