Abstract: Systems and methods to identify a filter set in a keyword query are described. The system receives a query from a client machine. The system identifies filter sets based on the query and a based on rules. The filter sets include a first filter set that includes a first filter. The rules are utilized to associate at the least one keyword from the query to the first filter. The system further scores the filter sets based on probabilities to generate scores. The probabilities describe occurrences of attribute-value pairs in listings that respectively describe items that were previously transacted on a network-based marketplace. The system further identifies the first filter set from the filter sets based on the scores, generates a user interface including search results that are identified based on the identified first filter set, and communicates the user interface, over the network, to the client machine.

Abstract: Systems and methods to seed a search are described. The system identifies a seed listing included in listings that describe items being offered for sale on a network-based marketplace. The system identifies a seed filter context based on the seed listing and probabilities. The probabilities describe occurrences of attribute-value pairs in a plurality of listings that respectively describe items that were previously transacted on the network-based marketplace. The system extracts values from the seed listing based on the seed filter context. The system initializes the seed filter context based on the values and generates search results based on the seed filter context. The search results include a second plurality of listings that are identified from the first plurality of listings. Finally, the system communicates interface information to a client machine including the seed filter context and at least one listing from the second plurality of listings.

Abstract: Methods and systems are provided to identify and present filters. The system receives a query, over a network, from a client machine and identifies a filter context based on the query. The filter context including a first plurality of filters. The system further identifies a second plurality of filters responsive the receiving the query. The identifying the second plurality of filters is based on the filter context and a plurality of probabilities. The system generates a user interface including search results that are identified based on the filter context. The system communicates the user interface, over the network, to the client machine.

Abstract: A system comprising a computer-readable storage medium storing at least one program and a computer-implemented method for providing recommendations are presented. Consistent with some embodiments, the method may include accessing a selection of queries executed on a database of items. The selection of queries may be used to retrieve a plurality of items from the database. The plurality of items may be grouped into one of multiple clusters based on similarities between items. The method may further include receiving a recommendation request related to an item corresponding to a first cluster of the multiple clusters. A recommendation may be generated using a related item selected from the first cluster.

Abstract: Aspects of the present disclosure include a system comprising a computer-readable storage medium storing at least one program and a computer-implemented method for providing alternative recommendations using search context. Consistent with some embodiments, the method may include receiving a search query and receiving a request regarding an item included in one or more search results providing in response to the search query. The method may further include determining an alternative item recommendation using the search query, and causing presentation of the alternative item recommendation.

Abstract: Aspects of the present disclosure include a system comprising a computer-readable storage medium storing at least one program and a computer-implemented method for providing alternative recommendations using search context. Consistent with some embodiments, the method may include receiving a user search query and receiving a request to view an item included in a set of search results retrieved in response to the search query. The method may further include determining an alternative item recommendation using the search query and attributes of the item, and causing presentation of the item and the alternative item recommendation in response to receiving the request to view the item.

Abstract: Systems and methods to identify a filter set in a keyword query are described. The system receives a query from a client machine. The system identifies filter sets based on the query and a based on rules. The filter sets include a first filter set that includes a first filter. The rules are utilized to associate at the least one keyword from the query to the first filter. The system further scores the filter sets based on probabilities to generate scores. The probabilities describe occurrences of attribute-value pairs in listings that respectively describe items that were previously transacted on a network-based marketplace. The system further identifies the first filter set from the filter sets based on the scores, generates a user interface including search results that are identified based on the identified first filter set, and communicates the user interface, over the network, to the client machine.

Abstract: Systems and methods to identify a filter set in a keyword query are described. The system receives a query from a client machine. The system identifies filter sets based on the query and a based on rules. The filter sets include a first filter set that includes a first filter. The rules are utilized to associate at the least one keyword from the query to the first filter. The system further scores the filter sets based on probabilities to generate scores. The probabilities describe occurrences of attribute-value pairs in listings that respectively describe items that were previously transacted on a network-based marketplace. The system further identifies the first filter set from the filter sets based on the scores, generates a user interface including search results that are identified based on the identified first filter set, and communicates the user interface, over the network, to the client machine.

Abstract: Systems and methods to identify values for a selected filter are described. The system receives a selection from a client machine. The selection identifies a filter that includes a first attribute-value pair that includes a first attribute and a first value, the first attribute-value pair being included in a concept query that was extracted from a query including at least one keyword that was received over the network from the client machine. The system further identifies filters responsive to receiving the selection, the identification of the filters being based on the first attribute and probabilities describing occurrences of attribute-value pairs in listings that respectively describe items that were previously transacted on a network-based marketplace, the filters including values. The system further generates a user interface including the values and search results that are identified based on the concept query and communicate the user interface to the client machine.

Abstract: Methods and systems are provided to identify and present filters. The system receives a query, over a network, from a client machine and identifies a filter context based on the query. The filter context including a first plurality of filters. The system further identifies a second plurality of filters responsive the receiving the query. The identifying the second plurality of filters is based on the filter context and a plurality of probabilities. The system generates a user interface including search results that are identified based on the filter context. The system communicates the user interface, over the network, to the client machine.

Abstract: Systems and methods to seed a search are described. The system identifies a seed listing included in listings that describe items being offered for sale on a network-based marketplace. The system identifies a seed filter context based on the seed listing and probabilities. The probabilities describe occurrences of attribute-value pairs in a plurality of listings that respectively describe items that were previously transacted on the network-based marketplace. The system extracts values from the seed listing based on the seed filter context. The system initializes the seed filter context based on the values and generates search results based on the seed filter context. The search results include a second plurality of listings that are identified from the first plurality of listings. Finally, the system communicates interface information to a client machine including the seed filter context and at least one listing from the second plurality of listings.

Abstract: Systems and methods to identify and present filters are described. The system receives a query from a client machine, the query including at least one keyword. The system further identifies a filter context based on the query, the filter context including a first set of filters including attribute-value pairs, the attribute-value pairs including a first attribute-value pair including a first filter and a second attribute-value pair including a second filter. The system further identifies a second set of filters responsive to receiving the query, the identifying the second set of filters is based on the filter context and probabilities describing occurrences of attribute-value pairs in listings that respectively describe items that were previously transacted on a network-based marketplace. The system further generates a user interface including search results that are identified based on the filter context and communicates the user interface to the client machine.

Abstract: Systems and methods to seed a search are described. The system identifies a seed listing included in listings that describe items being offered for sale on a network-based marketplace. The system identifies a seed filter context based on the seed listing and probabilities. The probabilities describe occurrences of attribute-value pairs in a plurality of listings that respectively describe items that were previously transacted on the network-based marketplace. The system extracts values from the seed listing based on the seed filter context. The system initializes the seed filter context based on the values and generates search results based on the seed filter context. The search results include a second plurality of listings that are identified from the first plurality of listings. Finally, the system communicates interface information to a client machine including the seed filter context and at least one listing from the second plurality of listings.

Abstract: Systems and methods of highlighting item listing features are disclosed. In some example embodiments, a request to display a first item listing on a computing device of a user is detected, with the first item listing having a plurality of features, and at least one feature from the plurality of features is selected based on user information associated with the user, in response to the detecting the request. The selected feature(s) is caused to be highlighted in a display of the first item listing on the computing device, with the highlighting of the selected feature(s) comprising at least one of displaying the selected feature(s) instead of the unselected ones of the plurality of features and applying a visual effect to the selected feature(s), with the application of the visual effect being distinct from a presentation of the unselected ones of the plurality of features.

Abstract: Systems and methods to identify and present filters are described. The system receives a query from a client machine, the query including at least one keyword. The system further identifies a filter context based on the query, the filter context including a first set of filters including attribute-value pairs, the attribute-value pairs including a first attribute-value pair including a first filter and a second attribute-value pair including a second filter. The system further identifies a second set of filters responsive to receiving the query, the identifying the second set of filters is based on the filter context and probabilities describing occurrences of attribute-value pairs in listings that respectively describe items that were previously transacted on a network-based marketplace. The system further generates a user interface including search results that are identified based on the filter context and communicates the user interface to the client machine.

Abstract: Systems and methods to identify values for a selected filter are described. The system receives a selection from a client machine. The selection identifies a filter that includes a first attribute-value pair that includes a first attribute and a first value, the first attribute-value pair being included in a concept query that was extracted from a query including at least one keyword that was received over the network from the client machine. The system further identifies filters responsive to receiving the selection, the identification of the filters being based on the first attribute and probabilities describing occurrences of attribute-value pairs in listings that respectively describe items that were previously transacted on a network-based marketplace, the filters including values. The system further generates a user interface including the values and search results that are identified based on the concept query and communicate the user interface to the client machine.

Abstract: Systems and methods to identify a filter set in a keyword query are described. The system receives a query from a client machine. The system identifies filter sets based on the query and a based on rules. The filter sets include a first filter set that includes a first filter. The rules are utilized to associate at the least one keyword from the query to the first filter. The system further scores the filter sets based on probabilities to generate scores. The probabilities describe occurrences of attribute-value pairs in listings that respectively describe items that were previously transacted on a network-based marketplace. The system further identifies the first filter set from the filter sets based on the scores, generates a user interface including search results that are identified based on the identified first filter set, and communicates the user interface, over the network, to the client machine.

Abstract: Aspects of the present disclosure include a system comprising a computer-readable storage medium storing at least one program and a computer-implemented method for providing alternative recommendations using search context. Consistent with some embodiments, the method may include receiving a user search query and receiving a request to view an item included in a set of search results retrieved in response to the search query. The method may further include determining an alternative item recommendation using the search query and attributes of the item, and causing presentation of the item and the alternative item recommendation in response to receiving the request to view the item.

Abstract: A system comprising a computer-readable storage medium storing at least one program and a computer-implemented method for providing recommendations are presented. Consistent with some embodiments, the method may include accessing a selection of queries executed on a database of items. The selection of queries may be used to retrieve a plurality of items from the database. The plurality of items may be grouped into one of multiple clusters based on similarities between items. The method may further include receiving a recommendation request related to an item corresponding to a first cluster of the multiple clusters. A recommendation may be generated using a related item selected from the first cluster.