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Segment-Search vs Knowledge Graphs: Making a Key-Word Search Engine for Web Documents

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Book cover Big Data Analytics (BDA 2019)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 11932))

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Abstract

It is becoming increasingly popular to publish data on the web in the form of documents. Segment-search is a semantic search engine for web documents. It presents a query language. It is suitable for skilled and semi-skilled domain experts, who are adept at the use of a specific collection of documents. It returns suitable documents selected by using document fragments, that satisfy user’s query. In contrast to knowledge graph approach, the technique is based on performing web page segmentation as per user perceived objects. Thus, it allows users’ to query without the knowledge of complex query languages or learning about the data organization schemes. The proposed system is scalable and can cater to large scale web document sources.

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Author information

Authors and Affiliations

  1. University of Aizu, Aizu-Wakamatsu, Fukushima, Japan

    Rashmi P. Sarode, Wanming Chu & Subhash Bhalla

  2. National Institute of Technology (NITD), Delhi, India

    Shelly Sachdeva

Authors
  1. Rashmi P. Sarode
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  2. Shelly Sachdeva
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  3. Wanming Chu
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  4. Subhash Bhalla
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Corresponding author

Correspondence to Subhash Bhalla .

Editor information

Editors and Affiliations

  1. Missouri University of Science and Technology, Rolla, MO, USA

    Sanjay Madria

  2. Harbin Institute of Technology, Shenzhen, China

    Philippe Fournier-Viger

  3. Ahmedabad University, Ahmedabad, India

    Sanjay Chaudhary

  4. International Institute of Information Technology, Hyderabad, India

    P. Krishna Reddy

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Sarode, R.P., Sachdeva, S., Chu, W., Bhalla, S. (2019). Segment-Search vs Knowledge Graphs: Making a Key-Word Search Engine for Web Documents. In: Madria, S., Fournier-Viger, P., Chaudhary, S., Reddy, P. (eds) Big Data Analytics. BDA 2019. Lecture Notes in Computer Science(), vol 11932. Springer, Cham. https://doi.org/10.1007/978-3-030-37188-3_6

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  • DOI: https://doi.org/10.1007/978-3-030-37188-3_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-37187-6

  • Online ISBN: 978-3-030-37188-3

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