Abstract: The specification discloses a computer-implemented method for user action determination, comprising: recognizing an item displacement action performed by a user; determining a first time and a first location of the item displacement action; recognizing a target item in a non-stationary state; determining a second time when the target item is in the non-stationary state and a second location where the target item is in the non-stationary state; and in response to determining that the first time matches the second time and the first location matches the second location, determining that the item displacement action of the user is performed with respect to the target item.

Abstract: The specification discloses a computer-implemented method for user action determination, comprising: recognizing an item displacement action performed by a user; determining a first time and a first location of the item displacement action; recognizing a target item in a non-stationary state; determining a second time when the target item is in the non-stationary state and a second location where the target item is in the non-stationary state; and in response to determining that the first time matches the second time and the first location matches the second location, determining that the item displacement action of the user is performed with respect to the target item.

Abstract: Enabling intelligent navigation is described, including: performing analysis of historical user activity data with respect to a query term to generate reference data associated with the query term; selecting a navigation recommendation model for the query term based at least in part on the reference data; using the reference data and the selected navigation recommendation model to determine a set of recommendation data associated with the query term, wherein the set of recommendation data includes at least a portion of a category system to be displayed in response to a subsequently received query including the query term.

Abstract: The present disclosure provides an information search method and apparatus. The information search method includes: receiving a search term input by a user; acquiring a search result based on the search term; acquiring description information corresponding to the search result; extracting one or more word segments from the description information; combining the one or more word segments to generate a title of the search result, where at least one word segment carries a hyperlink label; and returning the title after the combination of the word segments carrying the hyperlink labels to a user terminal for display. The method may facilitate a user to initiate a search, and may provide a relatively large number of search terms for the user to select from.

Abstract: Ranking product search results is disclosed, including: determining a plurality of sample pairs corresponding to a query word; determining a plurality of feature score values corresponding to a set of ranking features associated with the query word for each product associated with each of at least a subset of the plurality of sample pairs; and determining a set of weightings corresponding to the set of ranking features based at least in part on the plurality of feature score values and ranking priority assignments corresponding to the at least subset of the plurality of sample pairs.

Abstract: Enabling intelligent navigation is described, including: performing analysis of historical user activity data with respect to a query term to generate reference data associated with the query term; selecting a navigation recommendation model for the query term based at least in part on the reference data; using the reference data and the selected navigation recommendation model to determine a set of recommendation data associated with the query term, wherein the set of recommendation data includes at least a portion of a category system to be displayed in response to a subsequently received query including the query term.

Abstract: Enabling intelligent navigation is described, including: performing analysis of historical user activity data with respect to a query term to generate reference data associated with the query term; selecting a navigation recommendation model for the query term based at least in part on the reference data; using the reference data and the selected navigation recommendation model to determine a set of recommendation data associated with the query term, wherein the set of recommendation data includes at least a portion of a category system to be displayed in response to a subsequently received query including the query term.

Abstract: The present disclosure provides example methods and apparatuses of labeling product identifiers and methods of navigating products. Description information of one or more products is extracted. The description information of the products is clustered into a text. A subject analysis is applied to the text by using a text analysis method based on subject models to obtain one or more subjects and definition names for the subjects. A subject that is correlated to the description information of the product is used as an identifier of the product to label the product. The present techniques label the products with identifiers that have one or more user dimension attributes so that users may easily and intuitively find their desired products.

Abstract: A search request sent by a user is received to obtain one or more query words included in the search request. Historical operating information relating to a data object in a search result corresponding to the query words is conducted statistics. An attribute of the data object is selected as a specified attribute to generate a probability distribution model of the attribute value on the specified attribute of the data object. A respective probability corresponding to the attribute value of each data object on the specific attribute in the research result corresponding to the search request sent by the current user is calculated by using the probability distribution model. The output rank of the data objects in the search result is adjusted by using the probability. The present techniques improve reasonability of displaying the data objects in the search result and provide more accurate result.

Abstract: Ranking product search results is disclosed, including: determining a plurality of sample pairs corresponding to a query word; determining a plurality of feature score values corresponding to a set of ranking features associated with the query word for each product associated with each of at least a subset of the plurality of sample pairs; and determining a set of weightings corresponding to the set of ranking features based at least in part on the plurality of feature score values and ranking priority assignments corresponding to the at least subset of the plurality of sample pairs.

Abstract: The present disclosure provides example methods and apparatuses of labeling product identifiers and methods of navigating products. Description information of one or more products is extracted. The description information of the products is clustered into a text. A subject analysis is applied to the text by using a text analysis method based on subject models to obtain one or more subjects and definition names for the subjects. A subject that is correlated to the description information of the product is used as an identifier of the product to label the product. The present techniques label the products with identifiers that have one or more user dimension attributes so that users may easily and intuitively find their desired products.

Abstract: The present disclosure provides techniques for commodity property navigation. These techniques may determine, by a computing device, current corresponding property information of any product node in a product information database, and corresponding property information of each commodity under the product node. The computing device may add the property information to be updated into the current corresponding property information of the product node when property information to be updated exists. The computing device may then perform commodity property navigation by using the updated current corresponding property information of the product node. Using techniques of the present disclosure, mining and navigation of novel commodity properties may be implemented automatically, therefore solving problems (e.g., failure for timely updating commodity properties) associated with existing techniques.