Natural language processing

A survey of link up studies was conducted by the researchers in order to provide more brainstorm into the research in the field of an experimentation and to get support of the Borer-Moore string up searching algorithm as a relevant string duplicate algorithm that can be integrated with Natural Language Processing method and why it creates a better string searching process. The available literature related to the research work has been reviewed and presented under two distinct heads biz. railroad train Searching Algorithm ii) Natural Language Processing 2. 1. String Searching Algorithm There are many existing string matching algorithms, and each is efficient and effective in one way or another. It is worth noting that string is used interchangeably with text. It is a sequence of characters that may be a set of alphabet. The researchers have selected the Borer-Moore string matching algorithm because it is used in most software applications.String matching algorithms work by match ing two strings, the main string and the pattern. The main string is larger than or equal to the pattern that is the text being searched. Borer-Moore String matching algorithm works by comparing from right to left. It is fast because it skips some of the characters. It is efficient because with each failed attempt to match between the search string and the pattern, it uses the gathered information from that attempt to rule out as many positions where the pattern does not match. REF_002 It becomes faster if the set of alphabet is larger and the pattern is longerThe authoritative areas covered by natural speech communication touch are automatic summarization, coherence resolution, discourse analysis, machine translation, morphological segmentation, named entity recognition, natural engage generation, natural language understanding, optical character recognition, sentence breaking, sentiment analysis, speech recognition, speech segmentation, topic segmentation, word segmentation, wo rd sense disambiguation, information retrieval, information extraction and speech processing some other are stemming, text simplification, text-to-speech, text-proofing, natural language search, query expansion, automated essay scoring and truncating