Advanced Applications of Natural Language Processing for by Mário Rodrigues, António Teixeira

By Mário Rodrigues, António Teixeira

This booklet explains how should be created info extraction (IE) purposes which are capable of faucet the enormous quantity of proper details to be had in common language assets: web pages, respectable files similar to legislation and rules, books and newspapers, and social net. Readers are brought to the matter of IE and its present demanding situations and obstacles, supported with examples. The ebook discusses the necessity to fill the distance among files, information, and folks, and offers a huge evaluation of the know-how assisting IE. The authors current a prevalent structure for constructing structures which are in a position to the right way to extract correct info from ordinary language files, and illustrate the way to enforce operating structures utilizing state of the art and freely to be had software program instruments. The ebook additionally discusses concrete functions illustrating IE uses.

· presents an outline of cutting-edge expertise in details extraction (IE), discussing achievements and boundaries for the software program developer and supplying references for specialised literature within the area

· provides a accomplished checklist of freely on hand, prime quality software program for numerous subtasks of IE and for numerous normal languages

· Describes a widely used structure which can the best way to extract details for a given program domain

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Additional info for Advanced Applications of Natural Language Processing for Performing Information Extraction

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University of Pennsylvania working papers in linguistics 4, p 14 Martins AFT, Smith NA, Xing EP (2009) Concise integer linear programming formulations for dependency parsing. In: Proceedings of the joint conference of the 47th annual meeting of the ACL and the 4th international joint conference on natural language processing of the AFNLP, vol 1–vol 1. pp 342–350 Mcnamee P, Mayfield J (2004) Character n-gram tokenization for European language text retrieval. Inf Retr 7:73–97 Monroe W, Green S, Manning CD (2014) Word segmentation of informal Arabic with domain adaptation.

Intuitively it is possible to say that topics outside the scope of the application are not relevant information. For instance, if an application is about places to go on holidays it is not relevant to acquire information about cars. Also, information relevancy depends on the expertise of target audience. Information should be more detailed if the audience has a good grasp on the topic and less detailed otherwise. Having this into consideration implies that the proposed architecture should only extract information about topics explicitly required by the application, and with the same level of granularity specified by the ontology and seed examples.

All tools include methods for training new models from corpora. 2 Natural Language Toolkit (NLTK) NLTK (Bird et al. 2009) supports a wide range of text processing libraries, including text classification, tokenization, stemming, tagging, chunking, parsing, and semantic reasoning. It also provides intuitive interfaces to more than 50 corpora and lexical resources, including WordNet. It is well documented with tutorials, animated algorithms, problem sets, and is thoroughly discussed in a comprehensive book by Bird et al.

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