Knowledge-based e-catalog procurement system and method

Abstract

A flexible, intelligent electronic procurement method and system that emulates and learns from the adaptive behavior of a user trying to find a product in an electronic catalog. The invention allows for searching heterogeneous catalogs in virtually any format, and does not require pre-defined hierarchies, nor the pre-loading of vendor catalog contents, nor the scrubbing of vendor data. It does not impose fixed structures on the user, and it does not force the user to think like someone else. Instead, the invention allows the user to choose their own way to navigate a catalog of items, and then by recording successful search scenarios and storing that knowledge in a dynamic collection of search paths, the invention organically evolves. As the collection of search paths can be accessed by other users, the utility of the invention increases over time once implemented in a given environment.

Description

CROSS-REFERENCE TO RELATED APPLICATIONS[0001]This application is a Continuation of U.S. patent application Ser. No. 10 / 215,109, entitled “Knowledge-based e-catalog procurement system and method”, and filed Aug. 8, 2002, which claims priority to the provisional application:[0002]Knowledge-Based E-Catalog Procurement System and Method,[0003]Application No. 60 / 310,915, Filing Date Aug. 8, 2001[0004]Inventors G. C. Berkowitz, C. C. Wurtz, B. M. Roe.[0005]The above mentioned applications are incorporated herein by reference in their entireties.STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT[0006]Not ApplicableREFERENCE TO SEQUENCE LISTING, A TABLE, OR A COMPUTER PROGRAM LISTING COMPACT DISK APPENDIX[0007]Not ApplicableBACKGROUND OF THE INVENTION[0008]1. Field of the Invention[0009]The present invention is directed toward the field of electronic procurement systems. More specifically, the technology described in this patent application relates to a knowledge-based e-catalo...

AI Technical Summary

Benefits of technology

[0014]The invention, termed IntelleCat, is a knowledge-based e-catalog procurement assistant. It was created to solve problems encountered in the area of catalog management in electronic procurement systems. IntelleCat is intended to work closely with a major e-procurement system (e.g. Ariba, CommerceOne, Oracle) or as a stand-alone ordering system. It empowers procurement professionals to successfully search and find, retain purchasing expertise, and consistently implement best-practice procurements on a global scale.

[0025]Optimally, a solution was needed that is technologically feasible, functionally adaptive, easy to use, and cost-effective.

[0026]The solution needed to allow the data representations, which describe the item to be purchased, to be arbitrarily flexible. These data representations needed to be able to change over time without requiring onerous system administration. Additionally, the solution should capture the shopping process. Once a specific item has initially been located, subsequent searches for a similar, or an identical item, needed to be very fast and painless for the user. And lastly, this all needs to be accomplished without having to scrub vendor data.

[0027]The present invention's solution to the business problem is twofold. First, IntelleCat allows a much greater flexibility with regard to the format of the catalog data being loaded. Catalogs can be loaded and searched even if they are missing data fields. Furthermore, IntelleCat supports a virtually infinite variety of catalog data formats. Second, IntelleCat has a very intuitive and flexible search mechanism that also captures and shares search knowledge among all users of the system. Both aspects of IntelleCat are based on the idea of organic data structures that grow and adapt over time as they are used.

[0029]Different users may have different ways of thinking about the search hierarchy. IntelleCat stores all versions of trees that lead to the same result. The user is not, therefore, burdened by having to think like someone else. The consequence of this level of flexibility is that IntelleCat creates a rather large, complex forest of tree structures. IntelleCat is able to do this in a time- and space-efficient manner not only because of its proprietary architecture, but also through the use of various autonomous processes (named daemons) running behind the scenes, that continually prune and update the structures for optimum storage and navigation.

[0037]Is completely scalable and extensibleIntelleCat, while initially ignorant of corporate purchasing searches, will, over time, relieve the burden of painstaking manual searches for the majority of purchase requisitions.

Problems solved by technology

One of the most difficult problems facing B2B Internet commerce is the lack of consistent nomenclature across suppliers.

Although the Internet provides access to a large number of supplier catalogs (approximately 40-50% currently, with up to 90% coming online over the next 1-2 years), the effort required to locate a particular item is highly labor intensive.

In the case of Aspect, the solution is expensive.

Additionally, data must be preloaded, a task that represents a significant cost in data-entry person-hours.

Finally, the solution is costly to maintain, because as vendor catalogs change over time, additional data entry is required to change underlying databases.

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