System and methods for determining a desired listing using...

Data processing: database and file management or data structures – Database design – Data structure types

Reexamination Certificate

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C707S793000, C707S793000, C707S793000, C701S202000, C701S206000, C709S201000, C709S219000, C379S088200, C379S127030, C379S133000

Reexamination Certificate

active

06370523

ABSTRACT:

TECHNICAL FIELD
This invention generally relates to information retrieval and, more particularly described, relates to determining a desired listing, such as for a business, from a search using an intersection of coverage areas and a search region.
BACKGROUND OF THE INVENTION
The telephone rings and an employee answers the phone, “Hello, Acme Pizza Delivery. How may I help you?” The caller responds, “Yeah, I am starving. I am really craving a loaded pizza with the works. You know, pepperoni, sausage, mushrooms, peppers, extra cheese, onions, olives, and anchovies . . . and don't forget ham and extra garlic.” The caller proceeds to order several more pizzas, a full complement of drinks, and six orders of breadsticks. The employee finishes taking the order as the caller asks, “Can you deliver this stuff to my house?” The employee responds, “Sure we can deliver. What's your address?” The hungry caller says, “1234 East Broad Street.” “Oh. 1234 East Broad Street, huh? I'm sorry sir, we don't deliver in that area.” The silence is deafening. The caller cannot believe what he is hearing. “You will have to call one of our other stores that serves your location.” The caller, now frustrated at the prospect of giving the order again and still hungry, hangs up the telephone and tries to find the appropriate store that serves his location.
The caller in the above example may have avoided his frustration and quickly eased his hunger pains if he had used some type of information retrieval system to determine the closest business entity, such as a pizza delivery business, to serve his address. Using such a system, the caller may call a single number and, depending on the location associated with the caller's telephone number, the caller is connected with the closest business entity to serve the caller's location. Some businesses offering delivery services, such as pizza delivery businesses, employ such systems to avoid the exact customer dissatisfaction issues raised in the above example.
In more detail, when using the information retrieval system, the caller typically searches for information about the closest entity to serve the given location. The caller may be searching for information about the closest business, the closest governmental entity (such as a police station or fire station), or even the closest hospital. However, the usefulness of any such information retrieval system is dependent upon the accuracy of making the determination of the closest entity to serve the given location.
In one attempt to provide such an accurate determination, the determination of the closest business entity to serve a given location uses a pure distance calculation from the given location to the business entity. The pure distance is a point-to-point distance between coordinates of the given location and the coordinates of the business entity. However, using a pure distance from the given location to the business entity does not reflect the business' draw area for customers. A draw area (also called a coverage area) for a business is essentially the area in which the business can provide its goods or services to potential customers. For example, a business two miles away that only serves customers in a certain zip code area (not including the given separate location) may not be the closest business entity to serve the given location when a second business three miles away serves several counties, including the given location. Thus, using a pure distance to the given location may not always provide the most accurate determination of the closest business entity to serve a given location.
In another attempt to provide such an accurate determination, the closest business entity to serve a given location is determined by a search using predefined boundaries. Typically, such a system allows a caller (also more generally called a user) to search by predefined boundary (such as county, city, neighborhood, zip code, or other politically defined boundary) for the closest business entity serving the given location. Unfortunately, searching by predefined boundary can be inaccurate and problematic as well. For example, a close business serving the given location may be just outside the searched region (e.g., the searched county, city, neighborhood, or zip code) while being only a very short distance from the given location. The search simply misses the business due to the use of predefined boundaries. Thus, using predefined boundaries during a search for the closest business entity serving a given location may also lead to an inaccurate determination of the closest business entity serving the given location.
A system available from Southwestern Bell of San Antonio, Texas called the “Intellinumber” system allows a business to select a trade area or coverage area associated with a business. However, in the “Intellinumber” system, the trade area of the business is defined by standard ZIP+4 codes. The business is able to select a trade area that is then translated into a region defined by the standard ZIP+4 codes. When a caller uses the business' central number, the “Intellinumber” system matches the call with the appropriately defined trade area for the business. In this manner, the trade area of the business is simply a territory defined by predefined boundaries. This may become frustrating when a business' trade area is not accurately represented with predefined boundaries. As a result of the inaccurate representation, dependence upon predefined boundaries when defining a trade area of a business can also lead to an inaccurate determination of the closest entity to serve a given location.
In summary, there is a need for determining a closest business entity to serve a given location that (1) more accurately determines the closest entity, (2) does not depend upon predefined or, more particularly, politically established boundaries, (3) allows for arbitrary and customized definitions of coverage areas, and (4) allows for default definitions of coverage areas depending upon a categorization of the entity.
SUMMARY OF THE PRESENT INVENTION
The present invention is directed to a system and methods for determining a desired listing using an intersection of a search region and one or more coverage areas. In general, a desired listing is another term for a representation of the closest entity serving a given location or reference point. A coverage area is defined for each listing representing an entity, such as a business, a governmental unit (e.g., a police station, a library, a school, or a fire station), or a hospital. The listings and their associated coverage areas are maintained within an index to a database. The index is essentially a guide used to find data from within the database because each listing in the index is related to a specific record of data within the database. The listings are categorized within the index to make it easier to search for data related to the listings using the index.
The coverage area may be defined without regard to predefined boundaries and may be any arbitrary polygon shape. While a coverage area may be conveniently discussed in terms of a business' coverage area for listings associated with a particular type of business entity, those skilled in the art will quickly realize the applicability of the concepts of the present invention to other types of entities, such as defining a service coverage area for a hospital or a draw area for a school. Another example may be the service coverage area defined for a fire department. Thus, it is important to realize that the principles of the present invention are applicable when attempting to determine a desired one of several entities that provide goods or services to customers, users, or consumers.
Stated generally, the present invention provides a method for determining a desired listing from a group of listings using an intersection of a search region and coverage areas associated respectively with each of the listings. The general method begins by creating a d

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