Abstract: Using a processor, receiving, a query including a query image. A database is searched for a set of images similar to the query image, using a two-pass search. The results of the searching are then provided, the results including image members of the set of images similar to the query image. The first pass may be performed using a TF-IDF algorithm and the second pass ranks a predetermined number of results from the first pass by a best match algorithm or other type of algorithm. The type of second pass algorithm may be selectable by a user. If an end signal is not detected, a further two-pass search may be made based on a subsequent query having a subsequent query image. The subsequent query image may one of the results of the previous two pass search. A subsequent query image may change from an image of a product of a first product category to an image of a product of a second product category.

Abstract: Disclosed herein is a method, a system and a computer product for generating a snippet for an entity, wherein each snippet comprises a plurality of sentiments about the entity. One or more textual reviews associated with the entity is selected. A plurality of sentiment phrases are identified based on the one or more textual reviews, wherein each sentiment phrase comprises a sentiment about the entity. One or more sentiment phrases from the plurality of sentiment phrases are selected to generate a snippet.

Abstract: Methods and systems for enabling access to listing performance data, used in conjunction with a search engine to order search results, are described. Consistent with some embodiments, a listing performance data engine module processes API commands received from client computing systems. The data engine module processes the API commands to identify and communicate relevant listing performance data that is used by a listing performance algorithm to assign a listing performance score to item listings satisfying a search request. The listing performance data provides sellers who have items listed for sale an insight as to how their item listings are performing in comparison to other item listings.

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 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 assessing the quality of an item listing are described. In an example embodiment, a listing quality score for an item listing is derived as a weighted sum of first and second parts. The first part represents a predicted score based on a comparison of item attributes for the item listing that are known at listing time, with item attributes of similar item listings that have historical data available for assessing their actual performance. The second part is based on one or more observed demand metrics representing actual historical performance of the item listing. The weighting factor is derived, such that over time, the emphasis shifts from the predicted to the observed score.

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: 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: 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: Disclosed herein is a method, a system and a computer product for generating a snippet for an entity, wherein each snippet comprises a plurality of sentiments about the entity. One or more textual reviews associated with the entity is selected. A plurality of sentiment phrases are identified based on the one or more textual reviews, wherein each sentiment phrase comprises a sentiment about the entity. One or more sentiment phrases from the plurality of sentiment phrases are selected to generate a snippet.