Systems and methods of indexing and retrieving data

Details Systems and methods of indexing and retrieving data Systems and methods of indexing and retrieving data

2000-01-04

2001-06-05

Amsbury, Wayne (Department: 2771)

Data processing: database and file management or data structures

Database design

Data structure types

Reexamination Certificate

active

06243699

ABSTRACT:

BACKGROUND OF THE INVENTION
This invention relates to the field of wide access databases.
BACKGROUND
The Internet is by now the world's largest computer network, interconnecting millions of computers. One side effect of this large size is that the vast amount of information available on the Internet is often extremely difficult to access. Similar problems tend to occur on any wide access network, and in this discussion the Internet is used merely as an example of a wide access network.
Several attempts have been made to index the Internet, but each of these attempts has fallen short. One of the earliest attempts was to alphabetically index the names (URL addresses) of Internet users. Unfortunately, such an index is little more than an electronic “white pages,” and is generally only useful if one knows the exact name or address of the user to be contacted. A straight alphabetical index also provides little or no ability to access information by subject matter, unless the name happens to include an indication of the subject matter, as in “Bob's Pharmacy.” These shortcomings can be quite annoying when the amount of information is relatively small, and present profound difficulties as the amount of information grows.
Another attempt at indexing information on the Internet relies upon keywords. In keyword indices, users enter information into a freeform text field, and then the system, the system manager, or the user indexes key words found in the text. A considerable amount of scientific information is presently indexed in keyword indices such as Medline™. Although advantageous relative to URL indices, keyword indices are still impractical where the subject matter does not lend itself to keyword indexing. For example, if one is looking for a red colored automobile in a used car index, a keyword index would only be useful to the extent that all red cars are indexed according to the color red. Cars indexed as rose or magenta, crimson, ruby, vermilion or scarlet would not be located by a search for “red.” Moreover, as the number of records grows, keyword indices have seriously diminishing usefulness. For example, it does little good to conduct a search for red automobiles if the database locates 5000 records for red automobiles.
Still another attempt at indexing information on the Internet relies upon the use of specialty indices. In specialty indices the subject matter on a given database is limited to a particular type of product or service, and parameters are provided which specifically relate to that subject matter. Thus, a specialty real estate index may store data according to the parameters of property type (commercial, residential, undeveloped land, etc.), location, square footage, number of bedrooms, number of baths, style (Mediterranean, Cape Code, traditional, etc.), and price. Additional information may also be allowed in a comment or image field, but such information is typically not searchable or sortable, and is difficult to standardize. In addition, specialty indices are unable to properly handle multiple types of items, i.e., items which are generally described using inconsistent or otherwise different parameters. Thus, a real estate index is very poorly adapted for storing information relating to clothes or automobiles because the data parameters required for these items are almost completely inconsistent with the parameters useful for real estate.
One technique which has proven useful for organizing information relating to multiple types of items in a generic index is a hierarchical “yellow pages.” Thus, for example, the Big Book™ collects together Internet addresses for various categories such as attorneys, bookkeepers, florists and so on. The Big Book™ also indexes Internet addresses according to geographical location. Thus, one can select family law attorneys in Miami, rather than all attorneys, or all family law attorneys throughout the country. Despite these advantages, the “yellow pages” type of index is still not particularly useful where the subject matter one is searching for is not well categorized, or where the categories are vague or counterintuitive. For example, if one is searching for zipper manufacturers, a “yellow page” type index may not have any categories specifically for zippers, or zippers may be listed under some obscure category such as “interlocking clothing connectors.” Still further, such indices are notoriously cumbersome when searching for related products. For example, if one is searching for all types of clothing connectors, a “yellow pages” type of index may require separate searches for zippers, buttons, snaps, etc.
Similar problems exist with respect to limiting the searches by geographical location. For example, an index may well have categories for continents, countries, major metropolitan markets, or even specific cities, but a user must still discover on his own how the database treats a particular address such as “upstate” New York. In short, unless a user knows how the index is organized, it may be nearly impossible to find desired information in a convenient manner.
A better solution for organizing information in a generic index involves hierarchical sorting of products and services as is done by Netscape™ and others. In a hierarchical index one can begin with a high level category, and then logically work down to a lower level category by selecting choices from various menus. Thus, in selecting patent attorneys one might sequentially choose the following categories: Services (level 1), Business (level 2), Legal (level 3), Attorneys (level 4), and finally Patent (level 5). The same strategy can also be applied to geographical locations. One may, for example, select Los Angeles by choosing North America (level 1), United States (level 2), California (level 3), Southern California (level 4) and Los Angeles (level 5).
Even generic indices which select records hierarchically, however, are unsatisfactory for accessing huge amounts of information. One problem is that presently known hierarchical indices do not allow users to select smaller subsets of records, and to sort the selected records, based upon parameters having particular meaning for the field being searched. A search in the field of automobiles can be used to illustrate these shortcomings. If one searches a presently known Internet index for used Ford™ automobiles, one might locate thousands of cars for sale. Clearly that number is too large for a user to realistically review every listing. Even if the number of selected records could be reduced by limiting the subject matter to a particular model, or by limiting the geographical location to a particular city, there might still be several hundred cars for sale, and it would be a terrible waste of time to scan through each of those records if the user is only looking for cars with purchase prices of less than $3000. Specialty indices may allow a user to limit the search by price, color, body style, and other parameters all at the same time, but that capability is not available on generic indices which additionally cover other types of items, such as real estate and computers.
Even if generic indices could be developed that use different sets of parameters for different products, the creation costs of such an index would be enormous. There are millions of different types of products and services that need to be indexed, and if each type has five to ten different parameters, one would have to enter tens of millions of parameter-type pairs. This would be unrealistic not only from a labor standpoint, but also because it would be impossible for any given developer to understand all the different parameters applicable to all the different types of products. It is unclear, for example, just what appropriate parameters would be for various “chat rooms”. Only those individuals having interests in the relevant subject matters would likely know what parameters are best to use. Moreover, the parameters that are best for one person may be unsuitable for another person, and the most suitable parameters for any given subject

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