Informatics Publishing Limited

Kolla Bhanu Prakash ¹, M. A. Dorai Rangaswamy ², T. V. Ananthan ³, V. N. Rajavarman ³

Affiliations
1 Faculty of Computer Science Engineering, Sathyabama University, Chennai - 600 119, Tamil Nadu, IN
2 C.S.E & IT, AVIT, Chennai - 603104, Tamil Nadu, IN
3 Faculty of C.S.E, Dr.M.G.R.Educational & Research Institute, Chennai - 600 095, Tamil Nadu, IN

Abstract

Objectives: The objective is to develop a generic pixel-map based method to extract content in a short period of time for web documents. Method of Analysis: The method for extraction of content is in three levels, first level is in developing data inputs as attributes, second level in using the attributes to formulate a model and third level in interpretation of results. All three have variations so that validation comparison is possible for different parameters. Input data had all variations like language, script and usage and modeling is done using statistical, pattern recognition and ANN approaches. Findings: The method has demonstrated how quality and size of input data in the form of scalars, vectors and matrices affects the model and the result and this has been done for unstructured word sets chosen from web pages. The models chosen also give an idea of input/output variations in the outcome of the results. The uniqueness of the method is demonstrated for mono lingual, multi-lingual and transliterated datasets so that the applicability is universal. Novelty/Improvement: The method is generic in using pixel-maps, analytically stable in that the matrix input is used and versatility is demonstrated for adoption to different models.

Keywords

Data Mining Extraction, Image Processing Multilingual, Pre-processing, Segmentation, Unstructured

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S. Sruthi ¹, V. N. Rajavarman ¹

Affiliations
1 Dr.MGR Educational and Research Institute, Maduravoyal, Chennai-95, Tamil Nadu, IN

Abstract

Mobile Q&A systems, where mobile nodes access the Q&A systems through Internet, are very promising considering the rapid increase of mobile users and the convenience of practical use. However, such systems cannot directly use the previous centralized methods or broadcasting methods, which generate high cost of mobile Internet access, node overload, and high server bandwidth cost with the tremendous number of mobile users. Proposing a distributed Social-based mobile Q&A System (QSS) with low overhead and system cost as well as quick response to question askers. QSS enables mobile users to forward questions to potential answerers in their friend lists in a decentralized manner for a number of hops before resorting to the server. It leverages lightweight knowledge engineering techniques to accurately identify friends who are able to and willing to answer questions, thus reducing the search and computation costs of mobile nodes. It will give quick response for non-factual queries as well as colloquial languages.

Keywords

Centralized, Broadcasting, QsS, Non-Factual Queries, Colloquial.

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