Article

Experimental study of discovering essential information from customer inquiry

Authors:

Atsuhito Momma,

Koichi FurukawaAuthors Info & Claims

KDD '03: Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining

Pages 741 - 746

https://doi.org/10.1145/956750.956850

Published: 24 August 2003 Publication History

Abstract

This paper reports the result of our experimental study on a new method of applying an association rule miner to discover useful information from customer inquiry database in a call center of a company. It has been claimed that association rule mining is not suited for text mining. To overcome this problem, we propose (1) to generate sequential data set of words with dependency structure from the Japanese text database, and (2) to employ a new method for extracting meaningful association rules by applying a new rule selection criterion. Each inquiry in the sequential data was represented as a list of word pairs, each of which consists of a verb and its dependent noun. The association rules were induced regarding each pair of words as an item. The rule selection criterion comes from our principle that we put heavier weights to co-occurrence of multiple items more than single item occurrence. We regarded a rule important if the existence of the items in the rule body significantly affects the occurrence of the item in the rule head. The selected rules were then categorized to form meaningful information classes. With this method, we succeeded in extracting useful information classes from the text database, which were not acquired by only simple keyword retrieval. Also, inquiries with multiple aspects were properly classified into corresponding multiple categories.

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Cited By

Karmalkar PGurulingappa HMuhith JSinghal SMegaro GBuchholz F(2021)Improving Consumer Experience for Medical Information Using Text Analytics2021 International Symposium on Electrical, Electronics and Information Engineering10.1145/3459104.3459182(471-476)Online publication date: 19-Feb-2021
https://dl.acm.org/doi/10.1145/3459104.3459182
Shimazu KMori KMorita SOkumura Y(2014)4.1.1 A Case Study of the Effects of Platform Software Selection on Information System Maintenance Cost ‐ An Example of Enterprise Search System Establishment ‐INCOSE International Symposium10.1002/j.2334-5837.2009.tb00970.x19:1(593-606)Online publication date: 4-Nov-2014
https://doi.org/10.1002/j.2334-5837.2009.tb00970.x
Shimazu KMomma AFurukawa K(2003)Discovering Exceptional Information from Customer Inquiry by Association Rule MinerDiscovery Science10.1007/978-3-540-39644-4_23(269-282)Online publication date: 2003
https://doi.org/10.1007/978-3-540-39644-4_23

Index Terms

Experimental study of discovering essential information from customer inquiry
1. Applied computing
  1. Enterprise computing
    1. Business process management
  2. Operations research
    1. Marketing
2. Information systems
  1. Information systems applications
    1. Data mining

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Published In

cover image ACM Conferences

KDD '03: Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining

August 2003

736 pages

ISBN:1581137370

DOI:10.1145/956750

Conference Chair:
Lise Getoor
University of Maryland, College Park
,
General Chair:
Ted Senator
DARPA
,
Program Chairs:
Pedro Domingos
University of Washington
,
Christos Faloutsos
Carnegie Mellon University

Copyright © 2003 ACM.

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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Published: 24 August 2003

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KDD03: The Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

August 24 - 27, 2003

Washington, D.C.

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KDD '03 Paper Acceptance Rate 46 of 298 submissions, 15%;

Overall Acceptance Rate 1,133 of 8,635 submissions, 13%

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Cited By

Karmalkar PGurulingappa HMuhith JSinghal SMegaro GBuchholz F(2021)Improving Consumer Experience for Medical Information Using Text Analytics2021 International Symposium on Electrical, Electronics and Information Engineering10.1145/3459104.3459182(471-476)Online publication date: 19-Feb-2021
https://dl.acm.org/doi/10.1145/3459104.3459182
Shimazu KMori KMorita SOkumura Y(2014)4.1.1 A Case Study of the Effects of Platform Software Selection on Information System Maintenance Cost ‐ An Example of Enterprise Search System Establishment ‐INCOSE International Symposium10.1002/j.2334-5837.2009.tb00970.x19:1(593-606)Online publication date: 4-Nov-2014
https://doi.org/10.1002/j.2334-5837.2009.tb00970.x
Shimazu KMomma AFurukawa K(2003)Discovering Exceptional Information from Customer Inquiry by Association Rule MinerDiscovery Science10.1007/978-3-540-39644-4_23(269-282)Online publication date: 2003
https://doi.org/10.1007/978-3-540-39644-4_23

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