research-article

Leveraging web streams for contractual situational awareness in operational BI

Authors:

Malu Castellanos,

Chetan Gupta,

Song Wang,

Umeshwar DayalAuthors Info & Claims

EDBT '10: Proceedings of the 2010 EDBT/ICDT Workshops

Article No.: 7, Pages 1 - 8

https://doi.org/10.1145/1754239.1754248

Published: 22 March 2010 Publication History

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Abstract

The capability of correlating streaming web data with internal data in near real time gives enterprises a tremendous competitive advantage by enabling them to be aware of external events that can affect their business operations. This situational awareness gives business managers the opportunity to make informed operational decisions before it is too late. SIE-OBI is a platform being developed at HP Labs that responds to this need. In this paper we present an application of SIE-OBI to provide awareness of world events that could affect contractual relationships. We present the main components of the platform architecture and illustrate their functionality in the contractual situational awareness scenario.

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Cited By

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Pospiech MFelden C(2015)Towards a big data theory modelProceedings of the 2015 IEEE International Conference on Big Data (Big Data)10.1109/BigData.2015.7363990(2082-2090)Online publication date: 29-Oct-2015
https://dl.acm.org/doi/10.1109/BigData.2015.7363990
Cuzzocrea AJiang FLeung CLiu DPeddle ATanbeer S(2015)Mining Popular Patterns: A Novel Mining Problem and Its Application to Static Transactional Databases and Dynamic Data StreamsTransactions on Large-Scale Data- and Knowledge-Centered Systems XXI10.1007/978-3-662-47804-2_6(115-139)Online publication date: 17-Jul-2015
https://doi.org/10.1007/978-3-662-47804-2_6
IJntema WHogenboom FFrasincar FVandic D(2014)A Genetic Programming Approach for Learning Semantic Information Extraction Rules from NewsWeb Information Systems Engineering – WISE 201410.1007/978-3-319-11749-2_32(418-432)Online publication date: 2014
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Published In

EDBT '10: Proceedings of the 2010 EDBT/ICDT Workshops

March 2010

290 pages

ISBN:9781605589909

DOI:10.1145/1754239

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: 22 March 2010

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EDBT/ICDT '10

EDBT/ICDT '10: EDBT/ICDT '10 joint conference

March 22 - 26, 2010

Lausanne, Switzerland

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Overall Acceptance Rate 7 of 10 submissions, 70%

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Pospiech MFelden C(2015)Towards a big data theory modelProceedings of the 2015 IEEE International Conference on Big Data (Big Data)10.1109/BigData.2015.7363990(2082-2090)Online publication date: 29-Oct-2015
https://dl.acm.org/doi/10.1109/BigData.2015.7363990
Cuzzocrea AJiang FLeung CLiu DPeddle ATanbeer S(2015)Mining Popular Patterns: A Novel Mining Problem and Its Application to Static Transactional Databases and Dynamic Data StreamsTransactions on Large-Scale Data- and Knowledge-Centered Systems XXI10.1007/978-3-662-47804-2_6(115-139)Online publication date: 17-Jul-2015
https://doi.org/10.1007/978-3-662-47804-2_6
IJntema WHogenboom FFrasincar FVandic D(2014)A Genetic Programming Approach for Learning Semantic Information Extraction Rules from NewsWeb Information Systems Engineering – WISE 201410.1007/978-3-319-11749-2_32(418-432)Online publication date: 2014
https://doi.org/10.1007/978-3-319-11749-2_32
Leung CCuzzocrea AJiang F(2013)Discovering Frequent Patterns from Uncertain Data Streams with Time-Fading and Landmark ModelsTransactions on Large-Scale Data- and Knowledge-Centered Systems VIII10.1007/978-3-642-37574-3_8(174-196)Online publication date: 2013
https://doi.org/10.1007/978-3-642-37574-3_8
Frasincar FIJntema WGoossen FHogenboom F(2012)A Semantic Approach for News RecommendationBusiness Intelligence Applications and the Web10.4018/978-1-61350-038-5.ch005(102-121)Online publication date: 2012
https://doi.org/10.4018/978-1-61350-038-5.ch005
Leung CJiang F(2011)Frequent pattern mining from time-fading streams of uncertain dataProceedings of the 13th international conference on Data warehousing and knowledge discovery10.5555/2033616.2033642(252-264)Online publication date: 29-Aug-2011
https://dl.acm.org/doi/10.5555/2033616.2033642
Frasincar FBorsje JHogenboom F(2011)Personalizing News Services Using Semantic Web TechnologiesE-Business Applications for Product Development and Competitive Growth10.4018/978-1-60960-132-4.ch013(261-289)Online publication date: 2011
https://doi.org/10.4018/978-1-60960-132-4.ch013
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
Jensen CPedersen TThomsen C(2010)Multidimensional Databases and Data WarehousingSynthesis Lectures on Data Management10.2200/S00299ED1V01Y201009DTM0092:1(1-111)Online publication date: Jan-2010
https://doi.org/10.2200/S00299ED1V01Y201009DTM009
Castellanos MWang SDayal UGupta CElmagarmid AAgrawal D(2010)SIE-OBIProceedings of the 2010 ACM SIGMOD International Conference on Management of data10.1145/1807167.1807292(1105-1110)Online publication date: 6-Jun-2010
https://dl.acm.org/doi/10.1145/1807167.1807292
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