Data processing: database and file management or data structures – Database design – Data structure types
Reexamination Certificate
1999-06-25
2002-10-08
Von Buhr, Mari N. (Department: 2125)
Data processing: database and file management or data structures
Database design
Data structure types
C707S793000
Reexamination Certificate
active
06463431
ABSTRACT:
MICROFICHE APPENDIX
A microfiche appendix including 1 sheet of microfiche and 44 frames is included herewith.
BACKGROUND
A. Field of Invention
The present invention relates to database systems for evaluation of items according to user preferences, and more particularly to database systems using domain specific knowledge and utility functions to identify items meeting user defined criteria.
B. Background of Invention
The proliferation of computers and of the exploding use of the Internet have brought with them the increasing availability of computerized databases of products, information, and services from which users, such as consumers or professionals, evaluate and purchase such items. However, the ever increasing availability of such databases to more and diverse types of users has resulted in a widening gap between the existing and the user required skills for using these databases.
There exists sophisticated tools for database mining, analysis and the subsequent generation of information from the extracted data, but none of these tools allow users to quickly and efficiently perform a frequently desired task of finding in the database the item most suited to the user's objective and subjective preferences.
A typical activity involving this type of database access is online shopping: for example, a shopper is not interested in purchasing all of the VCRs that match her criteria, but only the one that gets closest to some “ideal VCR” defined by the user's own objective and subjective criteria (e.g., low cost, high performance, reliable, etc.). Conversely, even if no items match the shopper's search criteria, she might still be interested in purchasing the item that is ‘closest’ or most similar to the her criteria. Current database access tools do not meet the following needs of such users for the following reasons.
First, conventional databases will often return empty search result sets where no matches found are found to the set of specific criteria input by a user; alternatively, they may return too many matches where very few critieria are specified. In either case, the user is unable to identify which items are most similar to her overall criteria, and must reformulate her search criteria.
Second, compound queries where multiple attributes are specified and which result in empty projections do not tell which criterion or group of criteria were responsible for reducing the number of matches to zero. Conversely, when too many matches are found, conventional tools provide no indication of the sensitivity of the database to each criterion. Thus, the user is unable to modify her criteria to eliminate such criteria, but must proceed by trial and error.
Third, shoppers compare items not on the basis of a single criterion, but using the concept of similarity given all or most critieria. For example, a car buyer who has identified a first car as a suitable item, may be looking for a less expensive car which implicitly would not only have a lower price tag, but simultaneously retain all other desirable features of the first car as much as possible. However, current database tools have the ability to evaluate items only along one dimension (e.g., price) without regard for the overall similarity of items along multiple dimensions, and thus are not suitable for this buyer to identify such a similar alternative car with similar features to the first car.
Fourth, many domains (automobiles, computers, financial instruments) are very complex and require significant expertise to understand at the database level (“variable valve timing”, “256K cache”, “0.14 negative market correlation”). The typical consumer does not have sufficient expertise to evalute different items with respect to such technical data, but does know various high level critieria that are important to their decision making. The complexity of the underlying domain makes it difficult for a shopper to formulate a query that reflects his fuzzy needs and desires, resulting in a mismatch between the results the database provides and the user's actual needs.
Finally, many shoppers are unable to describe what they are looking for with defined search criteria, but they can identify which items do not satisfy their requirements when such items are presented to them. With conventional tools, such shoppers are unable to deconstruct the domain into its constituent components and define useful search criteria which can then be used to select items from the database for further evaluation.
Accordingly, it is desirable to provide a database system that supports analysis and evaluation of the similarity of items in the database with respect to multiple critieria.
SUMMARY OF THE INVENTION
The present invention, a Database Evaluation System (DES), is designed to help consumers and business users alike to find the item(s) in a database that most closely matches their objective requirements and subjective preferences. It effectively turns a database of information-rich items into an interactive buyer's guide.
The Database Evaluation System is a database technology focused entirely on the comparison and ranking of database items. The Database Evaluation System differs fundamentally from conventional database front ends in that it 1) uses a domain-specific vocabulary to isolate the user from potentially overwhelming amounts of raw data; 2) uses embedded expertise in the form of an “evaluation recipe” to guide the user along an optimal decision path; 3) provides a unique, interactive, real-time user interface for selection and navigation of items in the database; and 4) accounts for subjective, fuzzily defined user criteria.
In one embodiment, the DES of the present invention provides a system for constructing and evaluating items in a database storing any plurality of items. An authoring module enables the creation of a domain model which captures expert level knowledge about an application domain and maps the knowledge onto the database, thereby organizing the data into a useful and meaningful structure. More particularly, the authoring module creates a domain model including a hierarchical plurality of attributes in which some attribute are hierarchically defined by other attributes. For example in an automotive domain, an attribute such as performance may be hierarchically defined by attributes such as acceleration, braking, handling and the like. Each of these may be further hierarchically defined. For the lowest level attributes that are not defined by other attributes, the authoring module allows for the association of such attributes to selected fields of the database, which define the actual data stored therein. The authoring module also enables the expert to define for each attribute a transfer function that maps the values of the underlying field of the database to a utility value of the attribute. The authoring module also provide for weighting the attribute relative to other attributes, thereby weighting the utility values of one attribute relative to the utility values of other attributes. Multiple domain models may be defined for a given database, and applied by end users during access and selection of items from the database. This enables the user to apply the expert judgments of various experts to the same database of information.
The DES further includes an evaluation engine which couples a domain model to the database and provides various user interfaces for end users to access and evaluate items in the database. A first user interface receives from the user for selected attributes a user defined utility function that describes the utility of various values of the attribute for the user. The evaluation engine selects for retrieval and display items of the database according to both the user defined utility function and the utility values of the selected attributes as defined in the domain model. Fuzzy logic may be used to match the user defined utility functions with the domain model functions and database items values. The selected items are iteratively displayed in reponse to each partial input of sel
Bizrate.com
Ganz Law PC
Ganz, Esq. Bradley M.
Von Buhr Mari N.
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