Abstract:
Disclosed is a performance prediction system and service that uses acquired knowledge of queries that are received to make predictions concerning the future performance of certain entities, such as business entities. By analyzing query patterns and the actual or predicted performance of business entities, the performance prediction service is enabled to observe correlations between queries, query patterns and performance that can be used to facilitate the prediction of future performance.

Description:
TECHNICAL FIELD OF THE INVENTION  
       [0001]     This invention relates to a system, method and service that collects and stores information regarding queries received by a performance prediction system, and that enables the stored information to be queried to provide enhanced performance prediction results to a user.  
       BACKGROUND OF THE INVENTION  
       [0002]     Reputation and performance prediction systems are known and increasingly relied upon for providing valuable information. Examples include the Better Business Bureau, and Internet applications such as online auction and other types of user rating systems. Typically, these systems are intended to provide users with information about the reputation of businesses and/or the likely success of a transaction. To use these systems, a user typically requests pertinent information. In online embodiments, requests are typically submitted by sending queries of various kinds to the system, and receiving appropriate responses.  
         [0003]     If any information relating to the queries is retained, it is most likely used only in a limited fashion, such as for internal record-keeping and load-analysis purposes.  
         [0004]     What is needed is an improved performance prediction system that makes use of the received queries for providing additional and enhanced information to interested parties.  
       SUMMARY OF THE INVENTION  
       [0005]     The foregoing and other problems are overcome by methods and apparatus in accordance with embodiments of this invention.  
         [0006]     The inventors have recognized that valuable information can be learned from the queries received by a performance prediction system. The information can prove useful to businesses and other interested parties for gaining insight into the needs, interests and/or perspectives of system users. Information on trends and assorted other information may be produced as well from the query record. Examples of useful information include assessing the popularity of a product or service, and assessing the concerns of a typical customer.  
         [0007]     Disclosed herein are methods and apparatus for a performance prediction system and service. A typical user of the system disclosed herein may be a business, such as a manufacturer of goods for retail distribution. However, the class of potential users is not restricted to business entities, as other types of organizations and individuals may benefit from the use of this invention.  
         [0008]     Aspects of the teachings herein include a system for producing enhanced performance prediction information. The system includes a source of data that contains performance prediction data, where the data source is coupled to a query component adapted for execution of at least one query. Also provided is a data gathering component adapted for collecting query-relevant data concerning received queries and for storing the query-relevant data in a submitted query database. Also included is a meta-query component that is coupled to the submitted query database and that is adapted for querying the query-relevant data and for producing enhanced performance prediction information.  
         [0009]     In a further aspect of this invention, a performance prediction service uses acquired knowledge of the queries that are received to make predictions concerning the future performance of certain entities, such as business entities. By analyzing query patterns and the actual or predicted performance of business entities, the performance prediction service is enabled to observe correlations between queries, query patterns and performance that may be used to facilitate the prediction of future performance.  
         [0010]     Another aspect of the teachings herein includes a method for producing enhanced performance prediction information, by: querying a source of performance prediction data; collecting query-relevant data about each query; storing the query-relevant data; and, querying the query-relevant data for producing the enhanced performance prediction information.  
         [0011]     This invention also provides a computer program product stored on a computer readable media, for implementing a method to receive queries of performance prediction information, store query-relevant data derived from the queries, receive further queries directed to the query-relevant data, and provide the query-relevant data, and/or information derived from the query-relevant data, as enhanced performance prediction information.  
         [0012]     In a further aspect, this invention provides a service that is accessible over a data communications network, such as the Internet. The service is operable for receiving queries from users that are related to the performance of some entity, for storing query-relevant data derived from the queries, for receiving queries that are related to the stored query-relevant data, and for providing results for the queries of query-relevant data as enhanced performance prediction information to the users over the data communications network, or via some other means.  
         [0013]     Another aspect of this invention includes a communications device for receiving enhanced performance prediction information from a service, where the device includes a communications interface adapted for at least one of submitting a meta-query to the service and receiving the enhanced performance prediction information in response to a meta-query. In the preferred embodiment the service includes a source of data that includes performance prediction data, the data source being coupled to a query component adapted for receiving the meta-query and executing the meta-query; a data gathering component adapted for collecting query-relevant data for fulfilling meta-queries, and storing the query-relevant data in a submitted query database; and a meta-query component coupled to the submitted query database adapted for querying the query-relevant data to produce the enhanced performance prediction information in response to the reception of the meta-query from the communications device.  
         [0014]     The various embodiments of the invention described herein are illustrative only, and are not to be considered as limiting the scope or application of this invention. 
     
    
     BRIEF DESCRIPTION OF THE DRAWINGS  
       [0015]     The above set forth and other features of the invention are made more apparent in the ensuing Detailed Description of the Invention when read in conjunction with the attached Drawings, wherein:  
         [0016]      FIG. 1  is a block diagram that depicts components of a performance prediction service;  
         [0017]      FIG. 2  is a flow chart illustrating operation of the performance prediction service for providing a customer with performance prediction data; and  
         [0018]      FIG. 3  is a flow chart illustrating operation of the performance prediction service for storing performance prediction data. 
     
    
     DETAILED DESCRIPTION OF THE INVENTION  
       [0019]     Disclosed herein are methods and apparatus for an enhanced performance prediction data service. An “enhanced performance prediction data service,” as used herein, refers to a service for providing a user, such as an individual or an organization, with information concerning queries received by the performance prediction data service. An organization may be a for-profit or a not-for-profit organization, including government organizations. The performance prediction data service may be used by third parties, or it may be a “captive” service that is operated and used by a single individual or organization.  
         [0020]     “Performance prediction data” generally refers to data relevant to the operation of businesses and other organizations that is typically maintained in a database and made available to users through operation of one or more queries. Performance prediction data is so named as it is typically useful as an aid in predicting the reliability, performance, or some such aspect of a business or other organization. For the purposes of this invention “enhanced performance prediction data” generally refers to information that includes at least one component part that is derived from information descriptive of received queries for performance prediction data. Enhanced performance prediction data is so named as it is typically useful for providing insight not available in the performance prediction data, or for serving as an enhancement to the performance prediction data. Both performance prediction data and enhanced performance prediction data are generated and returned to a user in response to queries, which are referred to herein, for convenience only, as one of a “performance query” and a “meta-query.” 
         [0021]     In general terms, a performance query is directed to obtaining the performance prediction data, while a meta-query is directed to obtaining the enhanced performance prediction data. The performance prediction data is generated by querying a data source, such as a database of product information. The enhanced performance prediction information is derived from a stored historical record of previously received queries. The foregoing definitions are not to be construed as being limitations on the practice of this invention, and are provided simply for the sake of clarity and convenience.  
         [0022]      FIG. 1  illustrates one embodiment of a data processing system for implementing a performance prediction system  101 . In this embodiment, the system  101  communicates with a communications device  105  through a network  104 , such as the global Internet. Although illustrated as a PC terminal, the communications device  105  may include any type of device, including both mobile and fixed communications devices, capable of generating queries and/or meta-queries, and of receiving query and meta-query results from the system  101 . The communications device  105  is assumed to include a suitably programmed communications interface  105 A adapted for at least one of submitting a query, such as a meta-query, to the performance prediction system  101  and for receiving performance prediction and enhanced performance prediction information from the performance prediction system  101 .  
         [0023]     During operation of the system  101 , a user of the communications device  105  submits, via communications interface  105 A, a query  120  to the system  101 , seeking one of performance prediction information  125  or enhanced performance prediction information  135 . In this embodiment, where the user is seeking performance prediction information  125 , the query  120  is referred to as a performance query (PQ)  121 . If the user is seeking enhanced performance prediction information  135 , the query  120  is referred to as a meta-query (MQ)  122 . The system  101  determines the type of query  120 , and directs processing of the query  120  accordingly.  
         [0024]     The system  101  further includes a query component  110 , a data gathering component  112  and a performance prediction component  113 . The data gathering component  112  is bidirectionally coupled to the query component  110  and to a submitted query database  102 , containing submitted query-related data  132 . The performance prediction component  113  is bidirectionally coupled to the query component  110 , to the submitted query database  102 , and to a database of performance prediction information  103 , containing performance prediction data  133 .  
         [0025]     In the instance where the query  120  is the performance query  121 , the query is routed to the query component  110  for execution. The query component  110  operates with the data gathering component  112  and with the performance prediction component  113 . The data gathering component  112  gathers query-relevant information  132  about submitted performance queries  121 , and records the query-relevant information  132  in the submitted query database  102 . The performance prediction component  113  obtains data  132 ,  133  from the submitted query database  102  and the database of performance prediction information  103 , respectively, as necessary to satisfy the performance query  121 . The performance prediction component  113  may employ any suitable techniques for analyzing the data  132 ,  133 , such as statistical techniques, to obtain query patterns and correlations between query patterns. The performance prediction component  113  derives at least one of an actual or predicted performance of an entity of interest (such as a business or an individual), and may consider the correlations between queries, query patterns and performance to facilitate the prediction of future performance of the entity of interest. Results are returned to the query component  110  for routing to the communications device  105  as performance prediction information  125 .  
         [0026]     The meta-query component  111  provides for the submission of a second type of query  120 , the meta-query  122 , to request the enhanced performance prediction information  135 . The enhanced performance prediction information  135  is produced by querying query-relevant data  132  stored in the submitted query database  102 . Query-relevant data  132  may include a variety of data types, such as copies and/or numbers of individual received queries  120 , aggregations of query-related information (e.g., times and locations from which queries are received), and also the results of statistical analyses of queries  120 . The query-relevant data  132  may further include external information  130 , such as, in non-limiting examples, temporal information describing the date or time of query reception, and user location(s) and user-related identifying information (e.g., TCP/IP address). Combinations of such data may be provided as is determined suitable. Results are returned to the meta-query component  111  for routing to the communications device  105  as the enhanced performance prediction data  135 .  
         [0027]     The performance prediction information  125  and the enhanced performance prediction information  135  are typically routed to the communication device  105  submitting the query  120 , however, this is not required and the results may be directed elsewhere.  
         [0028]     As an example of performance prediction data  133  and query-relevant data  132 , one embodiment involves the non-limiting context of a manufacturer and/or distributor of retail goods. In this context, the user may request performance prediction information  125  such as the price of a certain item from a plurality of suppliers, an identification of competitive items, information related to durability and reliability, information related to complaints received from other users about the goods and/or the supplier of the goods, and other similar types of information. Another user may consider it important to obtain enhanced performance prediction information  135 , in order to gain insight into market trends in the interests of consumers, features that are of importance to consumers, the perception of the supplier in the eyes of consumers, and other similar types of information. The enhanced performance prediction information preferably includes an information component that is derived from the submitted query database  102  that contains the submitted query-related data  132 .  
         [0029]      FIG. 2  is a logical flow diagram illustrating an aspect of the operation of the performance prediction system  101 . When a query  120  is communicated to the system  101 , it is received in step  201 . The system  101  examines the query  120  and determines at step  202  the type of query. That is, whether the query  120  is a performance query  121  or a meta-query  122 . If the received query  120  is a meta-query  122 , then the query is sent to the meta-query component  111  for execution, otherwise it is sent to the query component  110 . At step  203  the query component  110  makes use of the submitted query database  102  and the database of performance prediction information  103 , as necessary to satisfy the performance query  121 . At step  204  the meta-query component  111  executes the meta-query  122  by reference to the submitted query database  102 .  
         [0030]     In the preferred embodiment information about the received query  120  is also recorded at step  205  in the submitted query database  102 , regardless of the type of query  120 , and query results are returned at step  206 . It should be recognized that at least some of the operations shown in  FIG. 2  may be rearranged, such as by executing step  205  prior to step  202 , or after step  206 .  
         [0031]      FIG. 3  is a logical flow diagram illustrating operation of a presently preferred embodiment of the system  101 . In step  301 , a performance query  121  is received by the query component  110 . The performance query  121  is satisfied in a two step process. First, the database of performance relevant information  103  is interrogated at step  302 , then the submitted query database  102  is interrogated at step  303 . At step  304  the performance query  121  is recorded in the submitted query database  102 . The result that is returned to the user in step  305  is, at least potentially, the result of considering information derived from previous queries  120 , which has been recorded in the submitted query database  102 . As was described with respect to  FIG. 2 , some of the steps may be rearranged, such as by executing step  304  prior to step  302 , or after step  205 , or by executing step  303  prior to step  302 .  
         [0032]     Another example of performance prediction data  133  and query-relevant data  132  involves the non-limiting context of a rating system. For example, in some on-line systems buyers and sellers can purchase goods or services, or can exchange goods or services, and can also rate various aspects of transactions. For example a potential buyer sends a performance query  121  to ascertain performance prediction information related to a potential seller. The returned information may include information related to the seller&#39;s reputation in previous transactions, customer satisfaction survey information, and other such data. The buyer or the seller using the system  101  may issue a meta-query  122  to ascertain enhanced performance prediction information. The enhanced information includes, for example, information descriptive of queries  120  received from previous potential buyers concerning the seller, queries received that included only the seller in the results, queries received that excluded the seller from the results, the number of queries received about the seller, copies of received queries, copies of results returned in response to received queries, how many queries were received during some prescribed period of time; patterns of queries received (e.g., queries received from specific locations, or from specific users), and correlations between queries.  
         [0033]     The system  101  supports techniques for producing enhanced performance prediction information  135  that includes at least one of: filtering query-relevant data  132 , aggregation of query-relevant data  132 , statistical analysis of query-relevant data  132 , and a search of query-relevant data  132  for locating information stored for a single query  121  (or for multiple queries  120 ). Accordingly, the examples herein are merely exemplary and not limiting of reporting results.  
         [0034]     Additional examples include embodiments where the results  125 ,  135  are filtered, or edited, so as to remove sensitive information, such as personal identification information. Filtering may occur at any stage, as appropriate. For example, the filtering may occur by foregoing the storage of certain data, by generally excluding an ability to query for certain data, or by excluding certain data when generating the query report. In other embodiments, the information  125 ,  135  is not filtered.  
         [0035]     The system  101  may include a discovery function  141  that enables users to obtain a list of companies that meet certain criteria.  
         [0036]     In a preferred embodiment the system  101  determines the identity and/or address of the user sending the query  120 , and establishes whether that user is authorized to access the system  101 , and/or arranges to charge the user for the service provided.  
         [0037]     Further examples of producing enhanced performance prediction information  135  include analysis of query-relevant data  132  to produce, as examples only, information that is descriptive or indicative of: the number of received queries that are about a specific user (possibly during some prescribed period of time); about a specific product; queries that include or exclude an item of interest (such as an identity of a business or a competitor of the business); queries that are indicative of trends; a most often asked question received in queries; queries that are about reliability (product and/or business); queries related to estimations of a success or failure of a transaction; and an average, a minimum, a maximum, and/or a count of queries containing a single (or multiple) specific subject(s).  
         [0038]     In additional embodiments of this invention, the meta-query component  111  allows users to register to be notified when certain information  132  comes to exist in the submitted query database  102 . For instance, a user might register to receive notification whenever some predetermined criteria has been reached, such as when a some number of queries  120  about the user have been recorded in the database  102 , or when any query is received about the user, or when some number of queries concerning a competitor have been recorded. A business user may also be interested in being informed whenever a query is received about a certain product that indicates that the buyer of the product may require service or repair of the product (e.g., a query is received from buyer requesting information about the availability of service or parts suppliers.  
         [0039]     In another embodiment, a user might register to automatically initiate a meta-query  122  at a specified time. In this case the meta-query may be already stored in the system  101 , and is activated at the appropriate time.  
         [0040]     As can be appreciated, in one aspect this invention enables the performance prediction system  101  to examine and analyze the submitted query database  102  that contains the submitted query-related data  132 . This can be seen to provide an ability to perform “data mining” on the submitted query-related data  132 , or more generally to permit a “query mining” operation to be performed.  
         [0041]     One skilled in the art should recognize that the invention is not limited to a performance prediction data system  101 , as disclosed herein, and that the teachings herein may be employed in a variety of embodiments. For example, a business may integrate the teachings herein with internal information systems, and therefore not deal with a service provider  101 . The teachings herein may be used as a part of a predictive maintenance information system, where maintenance planning or an engineering staff monitors access to information by maintenance personnel. The teachings herein may be implemented without a network  104  in a standalone system. Accordingly, it is considered that these and other additional embodiments are within the teachings of this invention, as defined by the appended claims.