Extracting Textual Information from Google Using Wrapper Class

A. Muthusamy; A. Subramani

doi:doi:10.11648/j.net.20170501.11

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Extracting Textual Information from Google Using Wrapper Class

A. Muthusamy, A. Subramani

Published in Advances in Networks (Volume 5, Issue 1)

Received: 22 April 2017 Accepted: 11 May 2017 Published: 5 July 2017

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Abstract

In general, the web text documents are often structured, un-structured, or semi-structured format that is promptly growing everyday with massive amounts of data. The users provided with many tools for searching relevant information. Some of the searches include, Keyword searching, topic and subject browsing can help users to find relevant information quickly. In addition, Index search mechanisms allow the user to retrieve a set of relevant documents. Occasionally these search mechanisms are not sufficient. With the rapid development of Internet, amount of data available on the web regularly increased, which makes it difficult for humans to distinguish relevant information. A wrapper class is proposed to extract the relevant text information and focus on finding useful facts of knowledge from unstructured web documents using Google. Techniques from information retrieval (IR), information extraction (IE), and pattern recognition are explored.

Published in	Advances in Networks (Volume 5, Issue 1)
DOI	10.11648/j.net.20170501.11
Page(s)	1-13
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2017. Published by Science Publishing Group

Keywords

Information Extraction, Retrieval, Semantic Web, Web Search Engine

References

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APA Style

A. Muthusamy, A. Subramani. (2017). Extracting Textual Information from Google Using Wrapper Class. Advances in Networks, 5(1), 1-13. https://doi.org/10.11648/j.net.20170501.11

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A. Muthusamy; A. Subramani. Extracting Textual Information from Google Using Wrapper Class. Adv. Netw. 2017, 5(1), 1-13. doi: 10.11648/j.net.20170501.11

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AMA Style

A. Muthusamy, A. Subramani. Extracting Textual Information from Google Using Wrapper Class. Adv Netw. 2017;5(1):1-13. doi: 10.11648/j.net.20170501.11

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@article{10.11648/j.net.20170501.11,
  author = {A. Muthusamy and A. Subramani},
  title = {Extracting Textual Information from Google Using Wrapper Class},
  journal = {Advances in Networks},
  volume = {5},
  number = {1},
  pages = {1-13},
  doi = {10.11648/j.net.20170501.11},
  url = {https://doi.org/10.11648/j.net.20170501.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.net.20170501.11},
  abstract = {In general, the web text documents are often structured, un-structured, or semi-structured format that is promptly growing everyday with massive amounts of data. The users provided with many tools for searching relevant information. Some of the searches include, Keyword searching, topic and subject browsing can help users to find relevant information quickly. In addition, Index search mechanisms allow the user to retrieve a set of relevant documents. Occasionally these search mechanisms are not sufficient. With the rapid development of Internet, amount of data available on the web regularly increased, which makes it difficult for humans to distinguish relevant information. A wrapper class is proposed to extract the relevant text information and focus on finding useful facts of knowledge from unstructured web documents using Google. Techniques from information retrieval (IR), information extraction (IE), and pattern recognition are explored.},
 year = {2017}
}

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TY  - JOUR
T1  - Extracting Textual Information from Google Using Wrapper Class
AU  - A. Muthusamy
AU  - A. Subramani
Y1  - 2017/07/05
PY  - 2017
N1  - https://doi.org/10.11648/j.net.20170501.11
DO  - 10.11648/j.net.20170501.11
T2  - Advances in Networks
JF  - Advances in Networks
JO  - Advances in Networks
SP  - 1
EP  - 13
PB  - Science Publishing Group
SN  - 2326-9782
UR  - https://doi.org/10.11648/j.net.20170501.11
AB  - In general, the web text documents are often structured, un-structured, or semi-structured format that is promptly growing everyday with massive amounts of data. The users provided with many tools for searching relevant information. Some of the searches include, Keyword searching, topic and subject browsing can help users to find relevant information quickly. In addition, Index search mechanisms allow the user to retrieve a set of relevant documents. Occasionally these search mechanisms are not sufficient. With the rapid development of Internet, amount of data available on the web regularly increased, which makes it difficult for humans to distinguish relevant information. A wrapper class is proposed to extract the relevant text information and focus on finding useful facts of knowledge from unstructured web documents using Google. Techniques from information retrieval (IR), information extraction (IE), and pattern recognition are explored.
VL  - 5
IS  - 1
ER  -

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Author Information

A. Muthusamy

Department of Computer Technology, N. G. P Arts and Science College, Coimbatore, India
A. Subramani

Department of Computer Science, Govt. Arts College, Dharmapuri, India

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APA Style

A. Muthusamy, A. Subramani. (2017). Extracting Textual Information from Google Using Wrapper Class. Advances in Networks, 5(1), 1-13. https://doi.org/10.11648/j.net.20170501.11

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ACS Style

A. Muthusamy; A. Subramani. Extracting Textual Information from Google Using Wrapper Class. Adv. Netw. 2017, 5(1), 1-13. doi: 10.11648/j.net.20170501.11

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AMA Style

A. Muthusamy, A. Subramani. Extracting Textual Information from Google Using Wrapper Class. Adv Netw. 2017;5(1):1-13. doi: 10.11648/j.net.20170501.11

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@article{10.11648/j.net.20170501.11,
  author = {A. Muthusamy and A. Subramani},
  title = {Extracting Textual Information from Google Using Wrapper Class},
  journal = {Advances in Networks},
  volume = {5},
  number = {1},
  pages = {1-13},
  doi = {10.11648/j.net.20170501.11},
  url = {https://doi.org/10.11648/j.net.20170501.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.net.20170501.11},
  abstract = {In general, the web text documents are often structured, un-structured, or semi-structured format that is promptly growing everyday with massive amounts of data. The users provided with many tools for searching relevant information. Some of the searches include, Keyword searching, topic and subject browsing can help users to find relevant information quickly. In addition, Index search mechanisms allow the user to retrieve a set of relevant documents. Occasionally these search mechanisms are not sufficient. With the rapid development of Internet, amount of data available on the web regularly increased, which makes it difficult for humans to distinguish relevant information. A wrapper class is proposed to extract the relevant text information and focus on finding useful facts of knowledge from unstructured web documents using Google. Techniques from information retrieval (IR), information extraction (IE), and pattern recognition are explored.},
 year = {2017}
}

Copy | Download

TY  - JOUR
T1  - Extracting Textual Information from Google Using Wrapper Class
AU  - A. Muthusamy
AU  - A. Subramani
Y1  - 2017/07/05
PY  - 2017
N1  - https://doi.org/10.11648/j.net.20170501.11
DO  - 10.11648/j.net.20170501.11
T2  - Advances in Networks
JF  - Advances in Networks
JO  - Advances in Networks
SP  - 1
EP  - 13
PB  - Science Publishing Group
SN  - 2326-9782
UR  - https://doi.org/10.11648/j.net.20170501.11
AB  - In general, the web text documents are often structured, un-structured, or semi-structured format that is promptly growing everyday with massive amounts of data. The users provided with many tools for searching relevant information. Some of the searches include, Keyword searching, topic and subject browsing can help users to find relevant information quickly. In addition, Index search mechanisms allow the user to retrieve a set of relevant documents. Occasionally these search mechanisms are not sufficient. With the rapid development of Internet, amount of data available on the web regularly increased, which makes it difficult for humans to distinguish relevant information. A wrapper class is proposed to extract the relevant text information and focus on finding useful facts of knowledge from unstructured web documents using Google. Techniques from information retrieval (IR), information extraction (IE), and pattern recognition are explored.
VL  - 5
IS  - 1
ER  -

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