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1 On sabbatical leave from NYU. Abstract Several pattern discovery methods proposed in the data mining literature have the drawbacks that they discover too many obvious or irrelevant patterns and that they do not leverage to a full extent valuable prior domain knowledge that decision makers have. In this paper we propose a new method of discovery that(More)
A drawback of most traditional data mining methods is that they do not leverage prior knowledge of users. In many business settings, managers and analysts have significant intuition based on several years of experience. In prior work [11, 12] we proposed methods that could discover unexpected patterns in data by using this domain knowledge in a systematic(More)
Recommending news articles has become a promising research direction as the Internet provides fast access to real-time information from multiple sources around the world. Traditional news recommendation systems strive to adapt their services to individual users by virtue of both user and news content information. However, the latent relationships among(More)
P revious work on the solution to analytical electronic customer relationship management (eCRM) problems has used either data-mining (DM) or optimization methods, but has not combined the two approaches. By leveraging the strengths of both approaches, the eCRM problems of customer analysis, customer interactions, and the optimization of performance metrics(More)
Clickstream data collected at any web site (site-centric data) is inherently incomplete, since it does not capture users' browsing behavior across sites (user-centric data). Hence, models learned from such data may be subject to limitations, the nature of which has not been well studied. Understanding the limitations is particularly important since most(More)
The work of Mannila et al. [4] of finding frequent episodes in sequences is extended to finding temporal logic patterns in temporal databases. It is argued that temporal logic provides an appropriate formalism for expressing temporal patterns defined over categorical data. It is also proposed to use Temporal Logic Programming as a mechanism for the(More)