By Mário Rodrigues, António Teixeira

This e-book explains how should be created info extraction (IE) functions which are capable of faucet the massive volume of suitable info to be had in average language assets: web pages, legitimate files corresponding to legislation and laws, books and newspapers, and social internet. Readers are brought to the matter of IE and its present demanding situations and boundaries, supported with examples. The ebook discusses the necessity to fill the space among records, info, and other people, and gives a extensive review of the know-how aiding IE. The authors current a universal structure for constructing structures which are capable of easy methods to extract correct info from typical language files, and illustrate find out how to enforce operating structures utilizing cutting-edge and freely to be had software program instruments. The publication additionally discusses concrete functions illustrating IE uses.

· offers an summary of cutting-edge know-how in details extraction (IE), discussing achievements and boundaries for the software program developer and offering references for specialised literature within the area

· provides a accomplished checklist of freely on hand, top of the range software program for a number of subtasks of IE and for numerous common languages

· Describes a established structure which could find out how to extract info for a given software domain

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2014). As for relations of more specialized domains, again, it can be difficult to find a ready to use software package, and again one 32 3 Identifying Things, Relations, and Semantizing Data Fig. 1 Two sentences with the same dependencies relating John Bardeen and the Nobel Prizes won exception is the biomedical domain where PIE the Search3 (Kim et al. 2012), MEDIE4 (Miyao et al. 2006), and MedInx (Ferreira et al. 2012; Teixeira et al. 2014) are relevant examples of such tools. 3 Getting Everything Together Having extracted the entities of the text and their respective relations is then necessary to store this information for later use in the context of the application (Cowie and Lehnert 1996).

Org Appelt DE (1999) Introduction to information extraction. Artif Intell Commun 12:161–172 Bird S, Klein E, Loper E (2009) Natural language processing with Python. O’Reilly, Sebastopol Brants T (1995) Tagset reduction without information loss. In: Proceedings of the 33rd annual meeting on Association for Computational Linguistics. pp 287–289 Chang AX, Manning CD (2014) TOKENS REGEX: defining cascaded regular expressions over tokens. Technical report CSTR 2014–02. Department of Computer Science, Stanford University, Stanford References 25 Chang P, Galley M, Manning CD (2008) Optimizing Chinese word segmentation for machine translation performance.

2004). Ontology editors are tools that provide assistance in the process of creation, manipulation, and maintenance of ontologies. They can work with various representation formats and, among other things, ontology editors provide ways to merge, visualize, and check the semantic consistence of ontologies (Noy et al. 2000). Protégé is an open-source tool developed at Stanford. Relevant features are the ability to assist users in ontology construction including importing and merging ontologies, the existence of several plugins that include alternative visualization mechanisms and alternative inference engines.

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