Abstract: As provided herein objects from a source catalog, such as a provider's catalog, can be added to a target catalog, such as an enterprise master catalog, in a scalable manner utilizing catalog taxonomies. A baseline classifier determines probabilities for source objects to target catalog classes. Source objects can be assigned to those classes with probabilities that meet a desired threshold and meet a desired rate. A classification cost for target classes can be determined for respective unassigned source objects, which can comprise determining an assignment cost and separation cost for the source objects for respective desired target classes. The separation and assignment costs can be combined to determine the classification cost, and the unassigned source objects can be assigned to those classes having a desired classification cost.

Abstract: Described is using modifiers in online search queries for queries that map to a database table. A modifier (e.g., an adjective or a preposition) specifies the intended meaning of a target, in which the target maps to a column in that table. The modifier thus corresponds to one or more functions that determine which rows of data in the column match the query, e.g., “cameras under $400” maps to a camera (or product) table, and “under” is the modifier that represents a function (less than) that is used to evaluate a “price” target/data column. Also described are different classes of modifiers, and generating the dictionaries for a domain (corresponding to a table) via query log mining.

Abstract: Described is a search-related technology in which context information regarding a user's prior search actions is used in making query recommendations for a current user action, such as a query or click. To determine whether each set or subset of context information is relevant to the user action, data obtained from a query log is evaluated. More particularly, a query transition (query-query) graph and a query click (query-URL) graph are extracted from the query log; vectors are computed for the current action and each context/sub-context and evaluated against vectors in the graphs to determine current action-to-context similarity. Also described is using similar context to provide the query recommendations, using parameters to control the similarity strictness, and/or whether more recent context information is more relevant than less recent context information, and using context information to distinguish between user sessions.

Abstract: As provided herein objects from a source catalog, such as a provider's catalog, can be added to a target catalog, such as an enterprise master catalog, in a scalable manner utilizing catalog taxonomies. A baseline classifier determines probabilities for source objects to target catalog classes. Source objects can be assigned to those classes with probabilities that meet a desired threshold and meet a desired rate. A classification cost for target classes can be determined for respective unassigned source objects, which can comprise determining an assignment cost and separation cost for the source objects for respective desired target classes. The separation and assignment costs can be combined to determine the classification cost, and the unassigned source objects can be assigned to those classes having a desired classification cost.