demonstration

READFAST: high-relevance search-engine for big text

Authors:

Michael Gubanov,

Anna PyaytAuthors Info & Claims

CIKM '13: Proceedings of the 22nd ACM international conference on Information & Knowledge Management

Pages 2465 - 2468

https://doi.org/10.1145/2505515.2508215

Published: 27 October 2013 Publication History

Abstract

Relevance of search-results is a key factor for any search engine. In order to return and rank the Web-pages that are most relevant to the query, contemporary search engines use complex ranking functions that depend on hundreds of features. For example, presence or absence of the query keywords on the page, their proximity, frequencies, HTML markup are just a few to name. Additional features might include fonts, tags, hyperlinks, metadata, and parts of the Web-page description. All this information is used by the search-engine to rank HTML Web pages returned to the user, but is unfortunately absent in free text that has no HTML markup, tags, hyperlinks, and any other metadata, except implicit natural language structure.

Here we demonstrate one of the first Big text search engines that leverages hidden structure of the natural language sentences in order to process user queries and return more relevant search-results than a standard keyword-search. It provides a structured index extracted from the text using Natural Language Processing (NLP) that can be used to browse and query free text.

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Cited By

Pavia SKhan RPyayt AGubanov MIves ZBonifati AEl Abbadi A(2022)Simplifying Access to Large-scale Structured Datasets by Meta-Profiling with Scalable Training Set EnrichmentProceedings of the 2022 International Conference on Management of Data10.1145/3514221.3520156(2377-2380)Online publication date: 10-Jun-2022
https://dl.acm.org/doi/10.1145/3514221.3520156
Islam KGubanov M(2021)Scalable Tabular Metadata Location and Classification in Large-Scale Structured DatasetsDatabase and Expert Systems Applications10.1007/978-3-030-86472-9_4(35-50)Online publication date: 31-Aug-2021
https://doi.org/10.1007/978-3-030-86472-9_4
Khan RGubanov Md'Aquin MDietze SHauff CCurry ECudre Mauroux P(2020)WebLensProceedings of the 29th ACM International Conference on Information & Knowledge Management10.1145/3340531.3417443(3425-3428)Online publication date: 19-Oct-2020
https://dl.acm.org/doi/10.1145/3340531.3417443
Show More Cited By

Index Terms

READFAST: high-relevance search-engine for big text
1. Information systems
  1. Information systems applications

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Information & Contributors

Information

Published In

cover image ACM Conferences

CIKM '13: Proceedings of the 22nd ACM international conference on Information & Knowledge Management

October 2013

2612 pages

ISBN:9781450322638

DOI:10.1145/2505515

General Chairs:
Qi He
LinkedIn, USA
,
Arun Iyengar
IBM T.J. Watson Research Center, USA
,
Program Chairs:
Wolfgang Nejdl
L3S Research Center, Germany
,
Jian Pei
Simon Fraser University, Canada
,
Rajeev Rastogi
Amazon, India

Copyright © 2013 Owner/Author.

Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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Publication History

Published: 27 October 2013

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CIKM'13: 22nd ACM International Conference on Information and Knowledge Management

October 27 - November 1, 2013

California, San Francisco, USA

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CIKM '13 Paper Acceptance Rate 143 of 848 submissions, 17%;

Overall Acceptance Rate 1,861 of 8,427 submissions, 22%

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Citations

Cited By

Pavia SKhan RPyayt AGubanov MIves ZBonifati AEl Abbadi A(2022)Simplifying Access to Large-scale Structured Datasets by Meta-Profiling with Scalable Training Set EnrichmentProceedings of the 2022 International Conference on Management of Data10.1145/3514221.3520156(2377-2380)Online publication date: 10-Jun-2022
https://dl.acm.org/doi/10.1145/3514221.3520156
Islam KGubanov M(2021)Scalable Tabular Metadata Location and Classification in Large-Scale Structured DatasetsDatabase and Expert Systems Applications10.1007/978-3-030-86472-9_4(35-50)Online publication date: 31-Aug-2021
https://doi.org/10.1007/978-3-030-86472-9_4
Khan RGubanov Md'Aquin MDietze SHauff CCurry ECudre Mauroux P(2020)WebLensProceedings of the 29th ACM International Conference on Information & Knowledge Management10.1145/3340531.3417443(3425-3428)Online publication date: 19-Oct-2020
https://dl.acm.org/doi/10.1145/3340531.3417443
Khan RGubanov M(2020)Towards Tabular Embeddings, Training the Relational Models2020 IEEE International Conference on Big Data (Big Data)10.1109/BigData50022.2020.9377769(5724-5726)Online publication date: 10-Dec-2020
https://doi.org/10.1109/BigData50022.2020.9377769
Podkorytov MGubanov M(2019)Hybrid.Poly: A Consolidated Interactive Analytical Polystore System2019 IEEE 35th International Conference on Data Engineering (ICDE)10.1109/ICDE.2019.00223(1996-1999)Online publication date: Apr-2019
https://doi.org/10.1109/ICDE.2019.00223
Soderman SKola APodkorytov MGeyer MGubanov MChampin PGandon FMédini LLalmas MIpeirotis P(2018)Hybrid.AICompanion Proceedings of the The Web Conference 201810.1145/3184558.3191600(1507-1514)Online publication date: 23-Apr-2018
https://dl.acm.org/doi/10.1145/3184558.3191600
Gubanov MPriya MPodkorytov MBarrett RCummings RAgichtein EGabrilovich E(2017)CognitiveDBProceedings of the 26th International Conference on World Wide Web Companion10.1145/3041021.3054735(207-211)Online publication date: 3-Apr-2017
https://dl.acm.org/doi/10.1145/3041021.3054735
Kola AMore HSoderman SGubanov M(2017)Generating Unified Famous Objects (UFOs) from the classified object tables2017 IEEE International Conference on Big Data (Big Data)10.1109/BigData.2017.8258537(4771-4773)Online publication date: Dec-2017
https://doi.org/10.1109/BigData.2017.8258537
Gubanov MStonebraker MBruckner D(2014)Text and structured data fusion in data tamer at scale2014 IEEE 30th International Conference on Data Engineering10.1109/ICDE.2014.6816755(1258-1261)Online publication date: Mar-2014
https://doi.org/10.1109/ICDE.2014.6816755

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