research-article

SIE-OBI: a streaming information extraction platform for operational business intelligence

Authors:

Malu Castellanos,

Song Wang,

Umeshwar Dayal,

Chetan GuptaAuthors Info & Claims

SIGMOD '10: Proceedings of the 2010 ACM SIGMOD International Conference on Management of data

Pages 1105 - 1110

https://doi.org/10.1145/1807167.1807292

Published: 06 June 2010 Publication History

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Abstract

Emerging business intelligence (BI) applications aim to provide situational awareness, i.e., information about real-world events that might affect the business operations of an enterprise. For instance, an enterprise might want to know whether customers are posting positive or negative comments about a new product it has just introduced; or whether some natural disaster affects its contracted suppliers. It is difficult to develop such applications today because they require extracting and correlating facts from multiple streaming and stored data sources, typically including unstructured data, which is not well supported by BI platforms today. In this paper, we describe SIE-OBI, a system that we are developing to enable the development and execution of such applications. We describe the novel features of this system, including a declarative interface for rapidly developing such applications, and a platform for optimizing and executing the applications. We illustrate its applicability through two use cases.

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Cited By

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Adnan KAkbar RWang K(2021)Development of Usability Enhancement Model for Unstructured Big Data Using SLRIEEE Access10.1109/ACCESS.2021.30891009(87391-87409)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2021.3089100
Hussain AAl-Turjman FSah M(2021)Semantic Web and Business Intelligence in Big-Data and Cloud Computing EraInnovations in Smart Cities Applications Volume 410.1007/978-3-030-66840-2_107(1418-1432)Online publication date: 13-Feb-2021
https://doi.org/10.1007/978-3-030-66840-2_107
Berlanga R(2018)Data Warehousing on Nonconventional DataEncyclopedia of Database Systems10.1007/978-1-4614-8265-9_80670(913-916)Online publication date: 7-Dec-2018
https://doi.org/10.1007/978-1-4614-8265-9_80670
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Index Terms

SIE-OBI: a streaming information extraction platform for operational business intelligence
1. Information systems
  1. Data management systems
    1. Database management system engines

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Published In

SIGMOD '10: Proceedings of the 2010 ACM SIGMOD International Conference on Management of data

June 2010

1286 pages

ISBN:9781450300322

DOI:10.1145/1807167

General Chair:
Ahmed Elmagarmid
Purdue University, USA
,
Program Chair:
Divyakant Agrawal
University of California at Santa Barbara, USA

Permission to make digital or hard copies of all or part 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 components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 June 2010

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SIGMOD/PODS '10

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SIGMOD

SIGMOD/PODS '10: International Conference on Management of Data

June 6 - 10, 2010

Indiana, Indianapolis, USA

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Overall Acceptance Rate 785 of 4,003 submissions, 20%

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Adnan KAkbar RWang K(2021)Development of Usability Enhancement Model for Unstructured Big Data Using SLRIEEE Access10.1109/ACCESS.2021.30891009(87391-87409)Online publication date: 2021
https://doi.org/10.1109/ACCESS.2021.3089100
Hussain AAl-Turjman FSah M(2021)Semantic Web and Business Intelligence in Big-Data and Cloud Computing EraInnovations in Smart Cities Applications Volume 410.1007/978-3-030-66840-2_107(1418-1432)Online publication date: 13-Feb-2021
https://doi.org/10.1007/978-3-030-66840-2_107
Berlanga R(2018)Data Warehousing on Nonconventional DataEncyclopedia of Database Systems10.1007/978-1-4614-8265-9_80670(913-916)Online publication date: 7-Dec-2018
https://doi.org/10.1007/978-1-4614-8265-9_80670
Berlanga R(2017)Data Warehousing on Non-Conventional DataEncyclopedia of Database Systems10.1007/978-1-4899-7993-3_80670-2(1-4)Online publication date: 5-Apr-2017
https://doi.org/10.1007/978-1-4899-7993-3_80670-2
Sotiropoulos YChatziantoniou D(2015)LinkViews: An Integration Framework for Relational and Stream SystemsEnabling Real-Time Business Intelligence10.1007/978-3-662-46839-5_5(65-80)Online publication date: 30-Apr-2015
https://doi.org/10.1007/978-3-662-46839-5_5
Löser ANagel CPieper SBoden C(2013)Beyond searchInformation Systems Frontiers10.1007/s10796-012-9403-815:3(311-329)Online publication date: 1-Jul-2013
https://dl.acm.org/doi/10.1007/s10796-012-9403-8
Berlanga RRomero OSimitsis ANebot VPedersen TAbelló AAramburu M(2012)Semantic Web Technologies for Business IntelligenceBusiness Intelligence Applications and the Web10.4018/978-1-61350-038-5.ch014(310-339)Online publication date: 2012
https://doi.org/10.4018/978-1-61350-038-5.ch014
Park BSong I(2012)Incorporating Text OLAP in Business IntelligenceBusiness Intelligence Applications and the Web10.4018/978-1-61350-038-5.ch004(77-101)Online publication date: 2012
https://doi.org/10.4018/978-1-61350-038-5.ch004
Viswanathan KGupta CLakshminarayan CHao MDayal UVennelakanti RHelm PRangaiah SSagiraju HDoddmani SSadaphal VHaritsa JDayal UDeshpande P(2011)An application of sensor and streaming analytics to oil productionProceedings of the 17th International Conference on Management of Data10.5555/2591338.2591356(1-8)Online publication date: 19-Dec-2011
https://dl.acm.org/doi/10.5555/2591338.2591356
Park BSong I(2011)Toward total business intelligence incorporating structured and unstructured dataProceedings of the 2nd International Workshop on Business intelligencE and the WEB10.1145/1966883.1966890(12-19)Online publication date: 25-Mar-2011
https://dl.acm.org/doi/10.1145/1966883.1966890
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