摘要:
Methods and system for social network analysis are described. In one embodiment, user interaction data of a time period for a plurality of users in a social network may be accessed. Network analysis may be performed on the user interaction data. A necktie-shaped graph may be generated from the user interaction data in accordance with the performing of the network analysis. The necktie-shaped graph may be utilized for analysis of the social network.
摘要:
A method and system analyze marketplace listing strategies. In some embodiments, the method accesses data associated with multiple marketplace listings. Each marketplace listing is associated with a product category. A state-action model, associated with the product category, is created based on the data associated with the multiple marketplace listings. The state-action model is then analyzed to identify a marketplace listing strategy associated with the product category.
摘要:
In one example embodiment, a system and method is shown that includes receiving a feedback score relating to a transaction engaged in by a user. The system and method also includes applying a weight to the feedback score based on weighting criteria to create a weighted feedback score. Further, generating a reputation score for the user based on the weighted feedback score may also be implemented. In an additional example embodiment, the system and method includes identifying a reputation score relating at least one neighbor of a user, the at least one neighbor of the user including another user with whom the user has engaged in a transaction. Further, the system and method includes ordering the reputation score relating to at least one neighbor of the user to create an ordered reputation score. Moreover, the system and method includes displaying the ordered reputation score.
摘要:
A method and system analyze data associated with a marketplace category. In some embodiments, a query is received that identifies a marketplace category from multiple marketplace categories associated with an electronic commerce marketplace. Data associated with the marketplace category is accessed and analyzed to identify multiple keywords used to identify listings in the marketplace category. A user interface is generated to display the analysis results, including at least a portion of the multiple keywords used to identify listings in the marketplace category.
摘要:
In various example embodiments, a system and method for personalization of search results are provided. In example embodiments, a query that triggers a search of a data storage device of a publication system that comprises a plurality of publications is received and a search performed to determine a result set of publications. Optimization preferences of the user are accessed and applied to the result set obtained based on the query to generate a personalized result set. The personalized result set is presented on a user interface of a device of the user.
摘要:
A method and system analyze data associated with a marketplace category. In some embodiments, a query is received that identifies a marketplace category from multiple marketplace categories associated with an electronic commerce marketplace. Data associated with the marketplace category is accessed and analyzed to identify multiple keywords used to identify listings in the marketplace category. A user interface is generated to display the analysis results, including at least a portion of the multiple keywords used to identify listings in the marketplace category.
摘要:
Methods and system for social commerce network analysis are described. In one embodiment, a strongly connected component value, an in-component value, an out-component value, a disconnected component value, a tendril value, and a tube value of a social network for a time period may be accessed. A social strength of the social network for the time period may be calculated by combining the strongly connected component value, the in-component value, the out-component value, the disconnected component value, the tendril value, and the tube value. The social strength of the social network for the time period may be utilized for analysis of the social network. The strongly connected component value may have a greatest weight and the disconnected component value may have the lowest weight in the combining.
摘要:
A method and system analyze session data. In some embodiments, the method accesses session data, identifies multiple sessions contained in the session data, and identifies multiple events that occurred within each of the multiple sessions. The method determines a temporal relationship between the multiple events in each session and analyzes the multiple sessions to aggregate events associated with the multiple sessions. The method then generates a graphical representation of the aggregated events.
摘要:
A method and system analyze marketplace listing strategies. In some embodiments, the method accesses data associated with multiple marketplace listings. Each marketplace listing is associated with a product category. A state-action model, associated with the product category, is created based on the data associated with the multiple marketplace listings. The state-action model is then analyzed to identify a marketplace listing strategy associated with the product category.
摘要:
Methods and system for social commerce network analysis are described. In one embodiment, a strongly connected component value, an in-component value, an out-component value, a disconnected component value, a tendril value, and a tube value of a social network for a time period may be accessed. A social strength of the social network for the time period may be calculated by combining the strongly connected component value, the in-component value, the out-component value, the disconnected component value, the tendril value, and the tube value. The social strength of the social network for the time period may be utilized for analysis of the social network. The strongly connected component value may have a greatest weight and the disconnected component value may have the lowest weight in the combining.