Abstract:
A system and method of identifying suspicious item-related features are disclosed. In some embodiments, a new item listing is received. The item listing may correspond to a request to list an item for sale on an e-commerce website. Item-related data for the item listing may be extracted. The item-related data can be used by a model to classify the new item listing. The model may be trained on data comprising identifications of which item listings in the sample of item listings are suspicious and identifications of which item listings in the sample of item listings are not suspicious may be received.
Abstract:
Disclosed is a system comprising a computer-readable storage medium storing at least one program, and a computer-implemented method for generating search results. A data access module accesses search results data indicative of a plurality items and that is indicative of ranking values of the plurality of items. A controller module generates page data based on the search results data. The controller module selects a first item from the plurality of items. A diversification module accesses a first rule of the page data. The diversification module determines a deviance value and a reordering-cost value of a second item from the plurality of items. The controller module can select, based at least on a first combination of the deviance and the reordering-cost values of the second item, the second item for placement ahead of the first item on the page data.
Abstract:
Disclosed are a system comprising a computer-readable storage medium storing at least one program, and a computer-implemented method for generating search results. A data access module accesses search results data indicative of a plurality items and that is indicative of ranking values of the plurality of items. A controller module generates page data based on the search results data. The controller module selects a first item from the plurality of items. A diversification module accesses a first rule of the page data. The diversification module determines a deviance value and a reordering-cost value of a second item from the plurality of items. The controller module can select, based at least on a first combination of the deviance and the reordering-cost values of the second item, the second item for placement ahead of the first item on the page data.
Abstract:
Disclosed is a system comprising a computer-readable storage medium storing at least one program, and a computer-implemented method for generating search results. A data access module accesses search results data indicative of a plurality items and that is indicative of ranking values of the plurality of items. A controller module generates page data based on the search results data. The controller module selects a first item from the plurality of items. A diversification module accesses a first rule of the page data. The diversification module determines a deviance value and a reordering-cost value of a second item from the plurality of items. The controller module can select, based at least on a first combination of the deviance and the reordering-cost values of the second item, the second item for placement ahead of the first item on the page data.
Abstract:
A system and method of identifying suspicious item-related features are disclosed. In some embodiments, a new item listing is received. The item listing may correspond to a request to list an item for sale on an e-commerce website. Item-related data for the item listing may be extracted. The item-related data can be used by a model to classify the new item listing. The model may be trained on data comprising identifications of which item listings in the sample of item listings are suspicious and identifications of which item listings in the sample of item listings are not suspicious may be received.
Abstract:
Techniques for determining search results based on session based refinements are presented herein. A method is disclosed that includes receiving a query in a user session, the query comprising one or more search parameters, detecting, in the user session and after receiving the query, a user event, updating, for each previous query in the user session that includes one or more of the search parameters, a record in a table for the query, the record storing a count of user events that match the user event, updating a score for each of the previous queries based on the count of user events, the respective records further storing the score, and ranking search results for a subsequent query based on the scores in the table, the subsequent query including the one or more search parameters.
Abstract:
Disclosed are a system comprising a computer-readable storage medium storing at least one program, and a computer-implemented method for generating search results. A data access module accesses search results data indicative of a plurality items and that is indicative of ranking values of the plurality of items. A controller module generates page data based on the search results data. The controller module selects a first item from the plurality of items. A diversification module accesses a first rule of the page data. The diversification module determines a deviance value and a reordering-cost value of a second item from the plurality of items. The controller module can select, based at least on a first combination of the deviance and the reordering-cost values of the second item, the second item for placement ahead of the first item on the page data.
Abstract:
Techniques for determining search results based on session based refinements are presented herein. A method is disclosed that includes receiving a query in a user session, the query comprising one or more search parameters, detecting, in the user session and after receiving the query, a user event associated with a property of an item, updating a record in a table that associates the query with the property, the table comprising a plurality of records that associate the query with respective item properties, the record comprising the query, the property, and a score, and ranking search results for a subsequent query based on the associated properties indicated in the plurality of records, the subsequent query including the one or more search parameters.
Abstract:
Systems and methods to predict bidding behavior are described. The system identifies a listing that includes listing information that describes an item that is being auctioned on a network-based marketplace. The system further identifies bid classification information based on the number of bids received for the item. Finally, the system predicts whether no more bids are expected to be received for the item based on the classification information.