2012 EfficientandDomainInvariantComp

• (Lappas et al., 2012) ⇒ Theodoros Lappas, George Valkanas, and Dimitrios Gunopulos. (2012). “Efficient and Domain-invariant Competitor Mining.” In: Proceedings of the 18th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (KDD-2012). ISBN:978-1-4503-1462-6 doi:10.1145/2339530.2339599

Subject Headings:

Cited By

• http://scholar.google.com/scholar?q=%222012%22+Efficient+and+Domain-invariant+Competitor+Mining
• http://dl.acm.org/citation.cfm?id=2339530.2339599&preflayout=flat#citedby

Quotes

Author Keywords

• Competitor mining; competitors; data mining; domain-invariant; miscellaneous

Abstract

In any competitive business, success is based on the ability to make an item more appealing to customers than the competition. A number of questions arise in the context of this task: how do we formalize and quantify the competitiveness relationship between two items? Who are the true competitors of a given item? What are the features of an item that most affect its competitiveness? Despite the impact and relevance of this problem to many domains, only a limited amount of work has been devoted toward an effective solution. In this paper, we present a formal definition of the competitiveness between two items. We present efficient methods for evaluating competitiveness in large datasets and address the natural problem of finding the top-k competitors of a given item. Our methodology is evaluated against strong baselines via a user study and experiments on multiple datasets from different domains.

References

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	Author	volume	Date Value	title	type	journal	titleUrl	doi	note	year
2012 EfficientandDomainInvariantComp	Dimitrios Gunopulos Theodoros Lappas George Valkanas			Efficient and Domain-invariant Competitor Mining				10.1145/2339530.2339599		2012