Ebay, Incorporated

Seema Shah

Jean-Michel Leon

Aditya Arora

Benjamin David Foster

Louis Marcel Gino Monier

Venkat Sundaranatha

Josh Loftus

Raghav Gupta

Srikanth Subramaniam

Vijay Raman

Suhail Ansari

Adam Nash

Xavier Stonestreet

Systems and methods to communicate information are described. The system receives a query and retrieves a set of data items from a database based on the query. The system generates a distribution based on a count of data items from the set of data items that were retrieved for each domain in a set of domains and a count of requests to view data items from another set of data items for each domain in the set of domains. The system identifies whether the distribution exhibits a type of a distribution by comparing the distribution with at least one of a peak distribution and a hills distribution. Finally, the system generates interface information based on the type of distribution.

Methods and systems to communicate information

There are provided methods and systems to identify an item based on data associated with the item. Information is received that is descriptive of an item to be listed on an information storage and retrieval platform. The information is associated with an aspect-value pair, which is an aspect of the item and a value of the aspect. An expression of an interest of a user in the item is received. The expression is associated with the aspect-value pair. In response to the associating of the expression with the aspect-value pair, the item is identified.

Identifying an item based on data associated with the item

There is provided a method and system to communicate information. The system receives a first query that contains a first constraint and retrieves a first plurality of data items from a database based on the first query. Next, the system generates a first distribution based on the first plurality of data items, the first distribution utilizing a first plurality of domains that are used to identify data items. Next the system generates a second distribution based on a plurality of requests to view a second plurality of data items. Next the system generates a third distribution based on the first distribution and the second distribution. Finally, the system generates distribution data to be included within an interface, the interface to include at least one interface element that is positioned on the interface based on the third distribution, the at least one interface element to respectively represent at least one domain.

There is provided methods and systems to identify a preferred domain of a plurality of domains corresponding to a query. First, the system receives the query. Second, the system accesses demand information corresponding to the query, the demand information including navigation information associated with the query. Third, the system accesses supply information corresponding to the query, the supply information including a count of data items in each of the plurality of domains that match the query. Fourth, the system identifies the preferred domain based on the demand information and the supply information.

Method and system to identify a preferred domain of a plurality of domains

There are provided methods and systems to enable navigation of data items based on aspect-value pairs extracted from the data items. First, a system receives a query, Second, the system identifies a plurality of data items found by the query. Third, the system identifies an aspect of at least one of the plurality of data items, Fourth, the system identifies a value of a plurality of values corresponding to the aspect. Fifth, the system receives a request to navigate to a set of data items within the plurality of data items, the request comprising the aspect and a requested value of the plurality of value. Each one of the set of data items has the aspect and the value. Sixth, the system presents, in a user interface, information about each one of the set of data items.

Method and system to enable navigation of data items

There is provided methods and systems to transform unstructured information into structured information. First, the system accesses a rule specifying a condition for assigning data to the data item, the condition based on the content of the data item, the assigned data to provide structure to the data item. Second, based on a detecting that the condition has been met, the system applies the rule to assign the assigned data to the data item. Third, the system stores, in a database, the data item and the assigned data as the data item structured information.

Method and system to transform unstructured information

There are provided methods and systems to identify an item based on data inferred from information about the item. Information is received that is descriptive of an item capable of being listed on an information storage and retrieval platform. The information is associated with an aspect-value pair, which is an aspect of the item and a value of the aspect and is inferred from the information. An expression of an interest of a user in an additional item is received. The expression is associated with the aspect-value pair. In response to the associating of the expression with the aspect-value pair, the item is identified as the additional item.

Identifying an item based on data inferred from information about the item

There is provided a method and system to communicate information. The system receives a first query that contains at least one constraint and retrieves a first plurality of data items from a database based on the first query. Next the system generating a first distribution based on the first plurality of data items, the first distribution utilizing a first plurality of domains used to identify data items. Next the system generates a second distribution based on a plurality of requests to view a second plurality of data items. Next the system generates a third distribution based on the first distribution and the second distribution. Finally the system generates interface information, to be communicated to a user, based on the third distribution.

A method and system to analyze rules is described. The system receives a query and applies a first plurality of rules to the query to identify a second plurality of rules that respectively identify at least one matching keyword in the query. Next, the system counts the first plurality of rules to identify a total quantity of rules applied to the query and further counts the second plurality of rules to identify a second quantity of rules that respectively identify at least one matching keyword in the query. Finally, the system determines a percentage of coverage for the query based on the total quantity of rules and the second quantity of rules.

Method and system to analyze rules

Methods and systems to analyze domain rules based on domain coverage of the domain rules are provided. First, the system receives a first plurality of data items from a database utilized by an information storage and retrieval platform, respectively counting the first plurality of data items to determine a total quantity of data items. Next, the system applies a plurality of rules to the first plurality of data items to identify a second plurality of data items associated with a first domain based on the respective rule, respectively counting the first plurality of data items to determine a first quantity of data items. Next, the system determines a percentage of coverage for the first domain, the percentage of coverage based on the first quantity of data items and the total quantity of data items. Next, the system represents the percentage of coverage as a first interface element within an interface.

Method and system to analyze domain rules based on domain coverage of the domain rules

Methods and systems to analyze aspect rules based on domain coverage of aspect-value pairs are provided. The system receives a first plurality of data items from a database, applies a first plurality of rules to the first plurality of data items to generate a second plurality of data items associated with a first domain, counts the second plurality of data items to determine a total quantity of data items, applies a second plurality of rules to the second plurality of data items to identify a third plurality of data items it associates with a first aspect-value pair, counts the third plurality of data items to determine a first quantity of data items, determines a percentage of coverage for the first aspect-value pair based on the first quantity of data items and the total quantity of data items, and provides the percentage coverage for the first aspect-value pair as an interface element within an interface.

Method and system to analyze aspect rules based on domain coverage of an aspect-value pair

Methods and systems to analyze aspect rules based on domain coverage of the aspect rules are provided. The system receives a first plurality of data items from a database, applies a first plurality of rules to the first plurality of data items to generate a second plurality of data items associated with a first domain, counts the second plurality of data items to determine a total quantity of data items, applies a second plurality of rules to the second plurality of data items to identify a third plurality of data items associated with a first aspect counts the third plurality of data items to determine a first quantity of data items, determines a percentage of coverage for the first aspect based on the first quantity of data items and the total quantity of data items, and provides the percentage of coverage as an interface element within an interface.

Method and system to analyze aspect rules based on domain coverage of the aspect rules

There are provided methods and systems to analyze rules. The system may analyze the rules by applying the rules to a most popular query. The most popular query may be identified as such by containing a particular keyword. Specifically, a most popular query may contain a keyword that appears more often than other keyword in a sample of queries received over a period of time. Next, the system applies the rules to the most popular query to determine a percentage of coverage of the rules for the most popular query. For example, a particular rule may evaluate TRUE, if the rule identifies a keyword in the query. Next the system generates a percentage of coverage based on a count of the rules that evaluated TRUE and the total number of rules that were applied to the most popular query.

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San Francisco, CA, United States of America

Seema Shah