Text Mining: Predictive Methods for Analyzing Unstructured by Sholom M. Weiss, Nitin Indurkhya, Tong Zhang, Fred Damerau

By Sholom M. Weiss, Nitin Indurkhya, Tong Zhang, Fred Damerau

One end result of the pervasive use of desktops is that the majority records originate in electronic shape. textual content mining—the technique of looking, retrieving, and examining unstructured, natural-language text—is excited about tips to make the most the textual information embedded in those documents.

Text Mining offers a finished advent and assessment of the sphere, integrating similar themes (such as man made intelligence and information discovery and knowledge mining) and delivering sensible suggestion on how readers can use text-mining the right way to study their very own info. Emphasizing predictive tools, the booklet unifies all key parts in textual content mining: preprocessing, textual content categorization, info seek and retrieval, clustering of files, and knowledge extraction. moreover, it identifies rising instructions for these seeking to do study within the region. a few historical past in info mining is useful, yet no longer essential.

Topics and features:

* provides a complete and easy-to-read advent to textual content mining

* Explores the applying and application of the equipment, in addition to the optimum suggestions for particular situations

* presents numerous descriptive case reviews that take readers from challenge description to procedure deployment within the genuine world

* makes use of tools that depend upon easy statistical innovations, therefore bearing in mind relevance to all languages (not simply English)

* contains entry to downloadable software program (runs on any computer), in addition to valuable chapter-ending historic and bibliographical feedback, an in depth bibliography, and topic and writer indexes

This authoritative and hugely available textual content, written by way of a crew of specialists on textual content mining, develops the basis strategies, ideas, and techniques had to extend past dependent, numeric info to computerized mining of textual content samples. Researchers, computing device scientists, and complex undergraduates and graduates with paintings and pursuits in facts mining, laptop studying, databases, and computational linguistics will locate the paintings a vital resource.

Show description

Read or Download Text Mining: Predictive Methods for Analyzing Unstructured Information PDF

Best data mining books

Mining of Massive Datasets

The recognition of the internet and web trade presents many tremendous huge datasets from which info should be gleaned by way of info mining. This e-book specializes in useful algorithms which were used to resolve key difficulties in facts mining and which are used on even the most important datasets. It starts off with a dialogue of the map-reduce framework, a huge device for parallelizing algorithms instantly.

Twitter Data Analytics (SpringerBriefs in Computer Science)

This short presents tools for harnessing Twitter information to find suggestions to advanced inquiries. The short introduces the method of gathering facts via Twitter’s APIs and provides recommendations for curating huge datasets. The textual content supplies examples of Twitter information with real-world examples, the current demanding situations and complexities of establishing visible analytic instruments, and the simplest techniques to handle those concerns.

Advances in Natural Language Processing: 9th International Conference on NLP, PolTAL 2014, Warsaw, Poland, September 17-19, 2014. Proceedings

This publication constitutes the refereed court cases of the ninth overseas convention on Advances in common Language Processing, PolTAL 2014, Warsaw, Poland, in September 2014. The 27 revised complete papers and 20 revised brief papers provided have been rigorously reviewed and chosen from eighty three submissions. The papers are geared up in topical sections on morphology, named entity reputation, time period extraction; lexical semantics; sentence point syntax, semantics, and computing device translation; discourse, coreference solution, automated summarization, and query answering; textual content type, info extraction and data retrieval; and speech processing, language modelling, and spell- and grammar-checking.

Analysis of Large and Complex Data

This ebook deals a photograph of the state of the art in class on the interface among facts, computing device technology and alertness fields. The contributions span a extensive spectrum, from theoretical advancements to useful purposes; all of them proportion a powerful computational part. the subjects addressed are from the next fields: information and information research; laptop studying and information Discovery; information research in advertising and marketing; information research in Finance and Economics; information research in medication and the existence Sciences; information research within the Social, Behavioural, and health and wellbeing Care Sciences; facts research in Interdisciplinary domain names; category and topic Indexing in Library and knowledge technological know-how.

Additional resources for Text Mining: Predictive Methods for Analyzing Unstructured Information

Sample text

Profits yes yes ... ... ... increased yes no ... ... ... earnings yes yes ... ... ... stock-price 1 0 ... 3. Abstract Spreadsheet for Predicting Stock Price about companies, and the labels are whether the stock price rose in some time period following the article. So far, we have not shied away from describing text as unstructured data that can be converted into structured data, where classical machine-learning methods can be applied. There remain many nuances in the recipe that do not alter this worldview but can make our trip to obtaining good results more direct.

Formulated in this way, the phrase identification problem is reduced to a classification problem for the tokens of a sentence, in which the procedure must supply the correct class for each token. Performance varies widely over phrase type, although overall performance measures on benchmark test sets are quite good. A simple statistical approach to recognizing significant phrases might be to consider multiword tokens. If a particular sequence of words occurs frequently enough in the corpora, it will be identified as a useful token.

A special issue of the Journal of Machine Learning Research, in 2003 was devoted to feature selection and is available online. One of the papers [Forman, 2003] presents experiments on various methods for feature reduction. A useful reference on word selection methods for dimensionality reduction is [Yang and Pedersen, 1997], which discusses a wide variety 46 2. From Textual Information to Numerical Vectors of methods for selecting words useful in categorization. It concludes that document frequency is comparable in performance to expensive methods such as information gain or chi-square.

Download PDF sample

Rated 5.00 of 5 – based on 17 votes