. Software requirements are usually written in natural language (NL) or speech language which is asymmetric and irregular. This paper presents a suitable method for transforming user software requirement specifications (SRS) and business designs written in natural language into useful object oriented models. Here a neoteric approach is proposed to generate object oriented items from SRS. For NL...

In the area of text mining, Natural Language Processing is an emerging field. As text is an unstructured source of information, to make it a suitable input to an automatic method of information extraction it is usually transformed into a structured format. Part of Speech Tagging is one of the preprocessing steps which perform semantic analysis by assigning one of the parts of speech to the give...

This paper describes a project tagging a spontaneous speech corpus with morphological information such as word segmentation and parts-ofspeech. We use a morphological analysis system based on a maximum entropy model, which is independent of the domain of corpora. In this paper we show the tagging accuracy achieved by using the model and discuss problems in tagging the spontaneous speech corpus....

Part of speech (POS) tagging is the process of assigning the part of speech tag or other lexical class marker to each and every word in a sentence. In many Natural Language Processing applications such as word sense disambiguation, information retrieval, information processing, parsing, question answering, and machine translation, POS tagging is considered as the one of the basic necessary tool...

Part of speech (POS) tagging is basically the process of automatically assigning its lexical category to each word according to its context and definition. Each word of sentence is marked in croups as corresponding to a particular part of speech like noun, verb, adjective and adverb. POS serves as a first step in natural language process applications like information extraction, parsing, and wo...

In this paper we describe a compression-based authorship verification model used in conjunction with a parts of speech tagger. We use standard language-specific parts of speech taggers on the texts in question to generate a stream of symbols representing each word, run the PPM (Prediction by Partial Matching) algorithm on the resulting stream, and use Bobicev’s method of calculating and compari...

Dependency parsing is a way of syntactic parsing and a natural language that automatically analyzes the dependency structure of sentences, and the input for each sentence creates a dependency graph. Part-Of-Speech (POS) tagging is a prerequisite for dependency parsing. Generally, dependency parsers do the POS tagging task along with dependency parsing in a pipeline mode. Unfortunately, in pipel...