Abstract: Methods and systems for using a demand metric for disambiguating a keyword entered from a user of a client machine, the keyword ambiguously identifying a product category, deriving a dominant product category that indicates the probable identity of the product category, and providing selectable images of aspects of the dominant product category for rendering at the client machine. Selection of one of the selectable images of aspects of the dominant product category disambiguates the identity of the ambiguously identified product category. Additional aspects of the disambiguated product category are then presented to the user.

Abstract: Methods and systems for simulating a search, for the purpose of evaluating one or more scoring functions used in ordering item listings for presentation in a search results page are described. Consistent with some embodiments, a simulation platform includes a real-time simulation module that receives search result sets for search queries that result in the conclusion of a transaction. The result set is then processed by the simulation platform with one or more test scoring functions, such that the resulting position of the item listing that has resulted in the transaction can be compared with the actual position at which the item listing was displayed in the actual search results. For each test scoring function, an average rank shift metric is determined, and displayed, thereby providing a metric with which to base decisions about which scoring functions to use in the production system.

Abstract: Methods and systems for using a demand metric for disambiguating a keyword entered from a client machine, the keyword identifying a product brand and ambiguously identifying a product category of the product brand; computing the dominant product category that indicates the probable identity of the product category; and providing signals representing selectable images of aspects of the dominant product category for rendering at the client machine.

Abstract: Described herein are methods and systems for promoting item listings that satisfy a query based on the item listings being assigned to certain categories that have, based on historical click data, exhibited high demand characteristics for the query. Consistent with some embodiments, a certain number of leaf-level categories are identified based on demand data for those categories, and the item listings assigned to those categories are promoted through a normalized weighting factor derived in part based on the click probability score associated with the category, clicks per impression rate, and weighted clicks per impression by ranking rate.

Abstract: Described herein are methods and systems for promoting item listings that satisfy a query based on the item listings being assigned to certain categories that have, based on historical click data, exhibited high demand characteristics for the query. Consistent with some embodiments, a certain number of leaf-level categories are identified based on demand data for those categories, and the item listings assigned to those categories are promoted through a normalized weighting factor derived in part based on the click probability score associated with the category, clicks per impression rate, and weighted clicks per impression by ranking rate.

Abstract: Methods and systems for analyzing, ordering and presenting item listings are described. In one example embodiment, a search query is processed to identify item listings satisfying the search query. Then, for each item listing that satisfies the search query, a ranking score is derived and assigned to the item listing. The ranking score is based in part on a relevance score, a listing quality score and a business rules score (or, adjustment factor). Finally, the item listings are ordered, based on their corresponding ranking score, and presented in order in a search results page.

Abstract: Methods and systems for analyzing, ordering and presenting item listings are described. In one example embodiment, a search query is processed to identify item listings satisfying the search query. Then, for each item listing that satisfies the search query, a ranking score is derived and assigned to the item listing. The ranking score is based in part on a relevance score, a listing quality score and a business rules score (or, adjustment factor). Finally, the item listings are ordered, based on their corresponding ranking score, and presented in order in a search results page.

Abstract: A method and system for determining an order of presentation of the search results is provided. An example system comprises a search request detector, a search engine, and an intermingler. The search request detector may be configured to receive a search request, and the search engine may be configured to determine search results based on the search request. The search results may comprise a first set of items of a first type and a second set of items of a second type. The number of items in the first set and the number of items in the second may reflect a predetermined target ratio. The intermingler may be configured to determine an order of presentation of the search results in a list of search results based on the target ratio.

Abstract: A method and system for determining an order of presentation of the search results is provided. An example system comprises a search request detector, a search engine, and an intermingler. The search request detector may be configured to receive a search request, and the search engine may be configured to determine search results based on the search request. The search results may comprise a first set of items in a first format and a second set of items in a second format. The number of items in the first set and the number of items in the second may reflect a predetermined target ratio and respective exposure percentages for items in the first format and items in the second format. The intermingler may be configured to determine an order of presentation of the search results in a list of search results based on the target ratio.

Abstract: Methods and systems for evaluating business rules for the purpose of promoting or demoting an item listing are presented. Consistent with an example embodiment, a conditional statement of a business rule that includes one or more expressions involving an item attribute and/or a seller attribute for an item listing is evaluated. If the conditional statement evaluates true, an adjustment factor set forth in the business rule is applied to a ranking score assigned to the item listing. The item listing is then presented in a search results page in a position relative to other item listings based upon the adjusted ranking score.

Abstract: Described herein are methods and systems for promoting item listings that satisfy a query based on the item listings being assigned to certain categories that have, based on historical click data, exhibited high demand characteristics for the query. Consistent with some embodiments, a certain number of leaf-level categories are identified based on demand data for those categories, and the item listings assigned to those categories are promoted through a weighting factor derived in part based on the click probability score associated with the category. In some embodiments, certain sub-categories may be selected when the demand associated with the child categories of the sub-category is well balanced.

Abstract: Various embodiments include a method and system for a seller conversion factor to ranking score for presented item listings. In an online marketplace with sellers and item listings, multiple-item item listings within fixed-price listings can be identified. The multiple-item item listings can each offer for sale a plurality of equivalent items and the multiple-item item listings can be a subset of item listings corresponding to a seller. An aggregate sales value can be calculated for each of the multiple-item item listings by identifying the number of sales corresponding to a multiple-item item listing. An impressions value can be calculated for the multiple-item item listings. An aggregate sales factor can be calculated using the aggregate sales value and the impressions value. The aggregate sales factor can be used as a component in an item listing quality score for some item listings of the seller.

Abstract: Described herein are methods and systems for promoting item listings that satisfy a query based on the item listings being assigned to certain categories. A query to identify a set of item listings is processed where each item listing associated with an item or service being offered for sale and assigned to a leaf-level category. The scope of the query is determined based on a dictionary of queries or a length of the query when the query is not found in the dictionary. One or more categories are identified based on the scope of the query. A search results page is presented with the item listings from the identified one or more categories.

Abstract: Methods and systems for using a demand metric for disambiguating a keyword entered from a client machine, the keyword identifying a product brand and ambiguously identifying a product category of the product brand; computing the dominant product category that indicates the probable identity of the product category; and providing signals representing selectable images of aspects of the dominant product category for rendering at the client machine.

Abstract: Various embodiments include a method and system for a seller conversion factor to ranking score for presented item listings. In an online marketplace with sellers and item listings, a first sum may be calculated by identifying a first set of item listings associated with the seller. A second sum may also be calculated by identifying a second set of item listings, where the second set is a subset of the first set and are successful item listings. Further, a conversion factor may be calculated from the first and second sums by dividing the second sum by the first sum. The conversion factor may then be used as a component in an item listing quality score for a third set of item listings associated with the seller.

Abstract: Methods and systems for using a half-life formula for deriving demand metrics used in ordering item listings, when presenting those item listings in a search results page, are described. In some embodiments, a demand metric for an item listing is derived by monitoring events associated with item listings, such as, keeping a count of the number of search impressions an item listing receives. A half-life formula is used to ensure that events occurring earlier in time contribute less to the demand metric than more recently occurring events. The demand metric are used to order the item listings, when the item listings are being presented in a search results page.

Abstract: Described herein are methods and systems for promoting item listings that satisfy a query based on the item listings being assigned to certain categories. A query to identify a set of item listings is processed where each item listing associated with an item or service being offered for sale and assigned to a leaf-level category. The scope of the query is determined based on a dictionary of queries or a length of the query when the query is not found in the dictionary. One or more categories are identified based on the scope of the query. A search results page is presented with the item listings from the identified one or more categories.

Abstract: Described herein are methods and systems for promoting item listings that satisfy a query based on the item listings being assigned to certain categories that have, based on historical click data, exhibited high demand characteristics for the query. Consistent with some embodiments, a certain number of leaf-level categories are identified based on demand data for those categories, and the item listings assigned to those categories are promoted through a normalized weighting factor derived in part based on the click probability score associated with the category, clicks per impression rate, and weighted clicks per impression by ranking rate.

Abstract: Various embodiments include a method and system for a seller conversion factor to ranking score for presented item listings. In an online marketplace with sellers and item listings, a first sum may be calculated by identifying a first set of item listings associated with the seller. A second sum may also be calculated by identifying a second set of item listings, where the second set is a subset of the first set and are successful item listings. Further, a conversion factor may be calculated from the first and second sums by dividing the second sum by the first sum. The conversion factor may then be used as a component in an item listing quality score for a third set of item listings associated with the seller.

Abstract: Described herein are methods and systems for promoting item listings that satisfy a query based on the item listings being assigned to certain categories that have, based on historical click data, exhibited high demand characteristics for the query. Consistent with some embodiments, a certain number of leaf-level categories are identified based on demand data for those categories, and the item listings assigned to those categories are promoted through a weighting factor derived in part based on the click probability score associated with the category. In some embodiments, certain sub-categories may be selected when the demand associated with the child categories of the sub-category is well balanced.