Data processing: database and file management or data structures – Database design – Data structure types
Reexamination Certificate
1998-05-04
2001-05-15
Amsbury, Wayne (Department: 2771)
Data processing: database and file management or data structures
Database design
Data structure types
C707S793000, C707S793000, C707S793000, C707S793000
Reexamination Certificate
active
06233571
ABSTRACT:
TECHNICAL FIELD
This invention pertains to computerized research tools. More particularly, it relates to computerized research on databases. Specifically, the invention indexes data, searches data, and graphically displays search results with a user interface.
BACKGROUND
Two manuals containing background materials are hereby incorporated by reference “V-Search Integration Tool Kit For Folio VIEWS”, containing thirty-six (36) pages, “V-Search Publisher's Tool Kit User's Manual”, containing one hundred sixty (160) pages.
Our society is in the information age. Computers maintaining databases of information have become an everyday part of our lives. The ability to efficiently perform computer research has become increasingly more important. Recent efforts in the art of computer research have been aimed at reducing the time required to accomplish research. Computer research on non-textual objects is very limited. Current computer search programs use a text-by-text analysis procedure (Boolean Search) to scan a database and retrieve items from a database. The user must input a string of text, and the computer evaluates this string of text. Then the computer retrieves items from the database that match the string of text. The two popular systems for computerized searching of data used in the legal profession are Westlaw™, a service sold by West Publishing Company, 50 W. Kellogg Blvd., P.O. Box 64526, St. Paul, Minn. 55164-0526, and Lexis™, a service sold by Mead Data Central, P.O. Box 933, Dayton, Ohio 45401.
However, Boolean searches of textual material are not very efficient. Boolean searches only retrieve exactly what the computer interprets the attorney to have requested. If the attorney does not phrase his or her request in the exact manner in which the database represents the textual object, the Boolean search will not retrieve the desired textual object. Therefore, the researcher may effectively by denied access to significant textual objects that may be crucial to the project on which the researcher is working. A second problem encountered with Boolean searches is that the search retrieves a significant amount of irrelevant textual objects. (It should be noted that in the context of research, a textual object could be any type of written material. The term textual object is used to stress the fact that the present invention applies to all types of databases. The only requirement that a textual object must satisfy in order to be selected by a Boolean search program is that part of the textual object match the particular request of the researcher. Since the researcher cannot possibly know all of the groupings of text within all the textual objects in the database, the researcher is unable to phrase his request to only retrieve the textual objects that are relevant.
Aside from the inefficiency of Boolean searches, the present systems for computerized searching of data are inadequate to serve the needs of a researcher for several other reasons. Even if one assumes that all the textual objects retrieved from a Boolean search are relevant, the listing of the textual objects as done by any currently available systems does not convey some important and necessary information to the researcher. The researcher does not know which textual objects are the most significant (i.e., which textual object is referred to the most by another textual object) or which textual objects are considered essential precedent (i.e., which textual objects describe an important doctrine).
In the legal research field, both Westlaw™ and Lexis™ have a Shepardizing™ feature that enables the researcher to view a list of textual objects that mention a particular textual object. The Shepardizing feature does not indicate how many times a listed textual object mentions the particular textual object. Although the Shepardizing feature uses letter codes to indicate the importance of a listed textual object (e.g., an “f” beside a listed textual object indicates that the legal rule contained in particular textual object was followed in the listed textual object), data on whether a listed textual object followed the rule of a particular textual object is entered manually by employees of Shepard's™/McGraw Hill, Inc., Div. of McGraw-Hill Book Co., 420 N. Cascade Ave., Colorado Springs, Colo. 80901, toll free 1-800-525-2474. Such a process is subjective and is prone to error.
Another legal research system that is available is the Westlaw™ key number system. The Westlaw™ key number system has problems similar to the shepardizing feature on the Lexis™ and Westlaw™ systems.
The video displays of both the West™ and Lexis™ systems are difficult to use. The simple text displays of these systems do not provide a researcher with all the information that is available in the database.
Computerized research tools for legal opinions and related documents are probably the most sophisticated computer research tools available and therefore form the background for this invention. However, the same or similar computer research tools are used in many other areas. For example, computer research tools are used for locating prior art for a patent application. The same problems of inefficiency discussed above exist for computer research tools in many areas of our society.
What is needed is a system for computerized searching of data that is faster than the available systems of research.
What is needed is a system for computerized searching of data that enables researchers to research in a manner in which they are familiar.
What is needed is a computerized research tool that will reorganize, re-index or reformat the data into a more efficient format for searching.
What is needed are more sophisticated methods to search data.
What is needed is a system for computerized searching of data that will significantly reduce the number of irrelevant textual objects it retrieves.
What is needed is a user friendly computerized research tool.
What is needed is a visual user interface which can convey information to a user conveniently.
What is needed is a system for computerized searching of data that easily enables the researcher to classify the object according to his or her own judgment.
What is needed is a system for computerized searching of data that provides a visual representation of “lead” objects and “lines” of objects, permitting a broad overview of the shape of the relevant “landscape.”
What is needed is a system for computerized searching of data that provides an easily-grasped picture or map of vast amounts of discrete information, permitting researchers to “zero in” on the most relevant material.
What is needed is a system for computer searching of data that provides a high degree of virtual orientation and tracking, the vital sense of where one has been and where one is going, and that prevent researchers from becoming confused while assimilating a large amount of research materials.
Accordingly, there is an unanswered need for a user friendly computerized research tool. There is a need for “intelligent” research technology that emulates human methods of research. There is a need in the marketplace for a more efficient and intelligent computerized research tool.
The present invention is designed to address these needs.
SUMMARY OF THE INVENTION
This invention is a system for computerized searching of data. Specifically, the present invention significantly aids a researcher in performing computerized research on a database or a network. The invention simplifies the research task by improving upon methods of searching for data including textual objects, and by implementing a user interface that significantly enhances the presentation of the data.
The invention can be used with an existing database by indexing the data and creating a numerical representation of the data. This indexing technique called proximity indexing generates a quick-reference of the relations, patterns, and similarity found among the data in the database. Using this proximity index, an efficient search for pools of data having a particular relation, pattern or
Cannon Shawn
Egger Daniel
Sauers Ronald D.
Amsbury Wayne
Dorsey & Whitney LLP
Egger Daniel
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