New PDF release: Advanced Techniques for Knowledge Engineering and Innovative

By Atsuko K. Yamazaki, Kaoru Eto, Akane Nakabayashi, Hitomi Shimada (auth.), Jeffrey W. Tweedale, Lakhmi C. Jain (eds.)

ISBN-10: 3642420168

ISBN-13: 9783642420160

ISBN-10: 3642420176

ISBN-13: 9783642420177

This e-book constitutes the completely refereed lawsuits of the sixteenth foreign convention on Knowledge-Based clever info and Engineering structures, KES 2012, held in San Sebastian, Spain, in September 2012. The 21 revised papers have been rigorously reviewed and chosen from 254 submissions. themes of curiosity contain the exploitation of AI thoughts, most up-to-date examine in info applied sciences and dynamic ontologies.

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Additional info for Advanced Techniques for Knowledge Engineering and Innovative Applications: 16th International Conference, KES 2012, San Sebastian, Spain, September 10-12, 2012, Revised Selected Papers

Example text

Relationship between term frequency and rankings: WiMAX related 4 Data Categorization Since blogs contain long sentences, it is difficult to apply text-mining techniques directly to raw textual data for semantic or structural classification. Moreover, it is difficult to find which factors in an information network are essential because an information network consists of several components. Taking the example phrase, “We need to spend a lot of time to access WiMAX”. Such phrase is always induced by the cause of networks/services, so the provider should quickly take measure against network components/services, otherwise increasing customer churn.

07:04:53. ” • There are also data that lack credibility. Therefore, the three main problems to solve are as follows: 1. How to extract words related to a given keyword in several long sentences. “Radio waves are of the most concern to WiMAX. ” The above sentence means that WiMAX connections were hard to establish two years ago, and it does not describe recent situations. 2. How to filter the possibility that the same message has been transmitted by a specific person. 3. How often to collect blog information (every month, quarterly, yearly, or when a new service is provided or a new product is released).

C. ): KES 2012, CCIS 246, pp. 25–38, 2013. c Springer-Verlag Berlin Heidelberg 2013 26 M. Tanaka-Yamawaki et al. data one by one, the RMT-PCA (RMT-based principal component analysis) can process all the “non-random” components at once by subtracting the RMT formula from the eigenvalue spectrum of a cross correlation matrix. Plerau, et al. [13] was one of the first attempts to apply this technique on stock price time series. By using the daily close stock prices of NYSE/S&P500, they successfully extracted eminent stocks out of massive data of price time series.

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Advanced Techniques for Knowledge Engineering and Innovative Applications: 16th International Conference, KES 2012, San Sebastian, Spain, September 10-12, 2012, Revised Selected Papers by Atsuko K. Yamazaki, Kaoru Eto, Akane Nakabayashi, Hitomi Shimada (auth.), Jeffrey W. Tweedale, Lakhmi C. Jain (eds.)


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