Microsoft Technology Licensing, LLC

Amazon Technologies, Inc.

Microsoft Corporation

Eric Anthony Reel

Gueorgui Chkodrov

Richard Zachary Jason

Ji-Rong Wen

Hua Yang

Madhu Madhava Kurup

Kong-Kat Wong

Kai Wu

David Shigeru Taniguchi

Daniel Takacs

Tong Yao

Jiyu Zhang

Jonathan R M Hart

Elishema Rose Fishman

Chun Yu

Gueorgui Bonov Chkodrov

Disclosed are various embodiments for identifying similar items in a data store by generating a modified query from a user supplied query and from information stored about particular item in the data store. Predetermined descriptive terms can be designated as useful for identifying items, and these terms can be located within keyword data for a particular item. Item correlations can also be identified with respect to a category designation of the item. The modified query can be generated based upon the predetermined descriptive terms in the item keyword data and the item correlations.

Generating modified query to identify similar items in a data store

Challenges associated with maintaining information about multiple instances of an activity are addressed. Separate database tables are maintained for data corresponding to active instances of an organization's activities and for data corresponding to inactive instances of an organization's activities. Multiple database tables can be maintained for data corresponding to inactive instances of an activity. In another aspect, data from the active instances table and one or more inactive instances tables are processed to generate combined analysis data.

Method for maintaining databases information about multiple instances of an activity generating, updating virtual OLAP cube based on modified star-schema

Aspects of the subject matter described herein relate to matching product information to products. In aspects, a product matching component receives product information. The product matching component normalizes the product information and obtains keywords from the product information. By querying a database of recognized products, the keywords are used to obtain a list of products that potentially match the product information. A confidence level is assigned to each of the potential matches in the list. A match may be returned for the highest matched product or for a selectable number of products whose confidence level(s) exceed a selectable threshold.

Scalable model-based product matching

Instance data is transmitted for Payload/Milestone events and for Enable-Continuation events. Payload/Milestone event data contains information describing an instance and/or providing a time of one or more portions of the processing of an instance. Included in the Enable-Continuation event data is an identifier associated with an instance by a first application and an identifier associated with the same instance by another application. The identifiers are placed in a continuation data table which is used to index the appropriate record of an instance data table. Out-of-order data for an instance is hidden from view until sequentially prior data for the instance is received.

Correlating process instance data across multiple applications

A system and method for performing click stream analysis is described. In one implementation, a Web log is processed to reconstruct a visit made by a user to a Web site. The Web log contains records representing actions performed by the user during the visit including any actions that may be designated a commerce event. A sequential identification is assigned to each record and the sequential identification is stored with the associated record in a database. Any records representing actions performed by the user that are designated as a commerce event are identified. The database is queried for a certain quantity of records representing actions performed by the user prior to and/or subsequent to the commerce event, based on the sequential identification assigned to each record.

System and method for performing click stream analysis

Multiple aggregation groups, which can be multiple partitions in an aggregated data table, are formed. Each group includes multiple aggregation records; each aggregation record includes an aggregation of values contained by a different subset of multiple database records. While an aggregation group is accessed by a single program thread during an aggregation group update transaction, no other threads are allowed to access that group. The aggregation groups are combined into a single table of aggregation records. Each of the multiple database records may correspond to an instance of an organizational activity and include a field having a value indicating the corresponding instance to be in one of several process states. Each aggregation group may further include time-sorted aggregation records, each time-sorted aggregation record containing an aggregation value for instances in one of the several process states during a time period associated with the time-sorted aggregation record. Aggregation records corresponding to instances completed outside of a preselected time window are deleted.

Maintaining time-sorted aggregation records representing aggregations of values from multiple database records using multiple partitions

Growing community of inventors

Seattle, WA, United States of America

Eric Anthony Reel