Abstract We present a new approach to Machine Translation evaluation based on the recently defined task Semantic Textual Similarity. Our approach explores lexical, syntactic and semantic machine translation evaluation metrics combined with distributional and knowledge-based word similarity metrics. Semantic sentence similarity evaluates give a progressively important role in text-related research and applications in areas such as text mining, Web page retrieval, and dialogue systems. This paper focuses mainly on computing the textual similarity between short texts of sentence length. It presents an algorithm that takes account of semantic textual information and word order information implied in the sentences.
For programming, however, the need for formal communication with the computer programming language has been granted. We want to challenge this assumption. MITCOE, Department of Computer Engineering, Pune 2015-16 1 Sentimental Analysis and Emotion Recognition We I think that modern natural language processing technology allows the fullest possible use of natural language programming ideas, thus greatly improving the programming non-professional user accessibility. To Feasibility displays of natural language programming, the paper tackles what is considered some of the most difficult situations: the steps and cycles. NLP is a field of computer science, artificial intelligence, and the computational linguistics are concerned with interactions between computers and human languages.
Basically CSPs is commonly used in the research of artificial intelligence and operations field. Due to high complexity, CSPs required the combination of heuristics and combinatorial search methods in order to solve it. BASIC MATHEMATICAL FORMULATION & CONSTRAINTS: Formally, a constraint satisfaction problem is defined as a triple , where is a set of variables, is a set of the respective domains of values, and is a set of constraints. is a variable in which each one can take on the values in the nonempty domain . While each constraint is in turn a pair , where is a subset of variables and is an - ary relation on the corresponding subset of domains .
Similarly word summarization is also just like a text summarization in which we will give the text as a paragraph and from that text we can find the word summary using Word Sense Disambiguation technique. 1.3 Word sense disambiguation Word Sense Disambiguation is a challenging technique in Natural Language Processing. There are some words in the natural languages which can cause ambiguity about the sense of the word. Those words are called polysemous words. Word sense disambiguation (WSD) is the solution to the problem.
NLP is interested in reciprocal interaction between man and machine. Since the NLP concerning with human (natural) languages, a lot of challenges have emerged in this area which is empowering computers to get which means from human or natural language data, and others include natural language era. The most prominent presented in this field what was published by Alan Turing in the fifties of the last century. Next paragraph will offer this aspect with more
Attention has been paid in the literature on bilingualism/multilingualism, in past reseraches on the phenomenon of code-switching. As a results of which different proposal are offered on different grammatical approaches to it. This article will attempt to discuss Poplack grammatical approach to code-switching. Language is a significant mode of communication between persons and it is hard to consider of a civilization without language. Language gives character to people‟s thoughts and controls their activities.
In a narrow sense, fuzzy logic can be defined as a logical system, which is an expansion of multi-valued logic. Whereas in a wider sense it is almost similar with fuzzy sets theory. It is a method for computing based on "degrees of truth or fact" rather than the "true or false" (1 or 0). The idea of fuzzy logic was first proposed by Dr. Lotfi Zadeh of the University of California at Berkeley in the 1965 [62]. 5.1 FUZZY LOGIC SYSTEM A fuzzy logic system (FLS) can be defined as the nonlinear mapping of an input data set to a scalar output data [63].
are the main challenges in Big Data. Data mining discover patterns from large data set. Data mining with Big data is a complex task. Here HACE theorem is proposed which finds Complex and Evolving relationships among data. It finds the characteristics
OWL build on RDF and RDF (s) adds more vocabulary to describe the properties and relationship among the classes with higher typing of properties and characteristic properties in building ontology (Horridge, Knublauch, Rector, Stevans, & Wroe, 2004). • Tools Ontology development tools facilitate the process of development and the reuse of ontologies. The most relevant tools to facilitate the development of ontologies are listed in Table 1 with a summary description, the name of tool, purposes, pricing policy and software architecture and backup management. Table 1 List of Ontology Tools Ontology Tool Purpose Pricing Policy and Software Architecture Backup Management Ontolingua To ease the development of Ontolingua ontologies in a shared environment between distributed groups Free Web access Client/Server No WebOnto To support the collaborative browsing, creation and editing ontologies Free Web access 3-tier
Within the industry of linguistics the explanations of language vary, and speakers vary in approach according to the definition they use. Those who research language as written interaction are interested in the dwelling of what they call “text”—how phrases and their areas are organized into consistent wholes—and concerned with how one language can be perfectly converted into another. In the area of machine translation, computers handle the large amount of data needed for such research. Relative speakers seek to identify families of 'languages' originated from a frequent ancestor. Structural and illustrative speakers perspective verbal language as having a ordered framework of three levels: seems to be, audio mixtures (such as words), and term mixtures (sentences).