Microsoft Technology Licensing, LLC

Assembly, Inc.

Zhaohui Tang

Pyungchul Kim

Scott Conrad Oveson

C James MacLennan

David Earl Heckerman

David Maxwell Chickering

Robert L Rounthwaite

Alexei V Bocharov

Raman S Iyer

Rong Jian Guan

Ioan Bogdan Crivat

Amir Netz

Ying Li

Irina Gorbach

Ming Zhou

Li Erran Li

Brian Burdick

Chin-Yew Lin

Cheng Niu

Donald Munro Farmer

Hai Huang

Pyunchul Kim

Faru Nie

A computer-implemented process includes receiving with an eCommerce platform from a user over a network a first product-search keyword, generating to a display of the user a graphical user interface (GUI) including a first selectable icon showing the first keyword, a first selectable image of a first product and a first connector between the first icon and first image, the first connector indicating that the first product was previously purchased using the eCommerce platform in response to the platform receiving the first keyword, and in response to user selection of the icon, generating to the GUI a set of performance indicators characterizing an advertising campaign associated with at least one of the first keyword and first product within the eCommerce platform.

Query-product interface for ecommerce platform

Systems, methods, and computer-readable media for dynamically generating text associated with an advertisement are provided. Core text associated with an advertisement is received from an advertiser, as is at least one attribute relevant to the advertiser and/or a user. Based upon the received attribute(s), it is determined whether customization of the core text is desired. If customization is desired, the core text is modified and presented in association with the advertisement. If customization is not desired, the core text is presented in association with the advertisement. In one embodiment, target advertisement placement information may also be utilized to determine whether customization of the core text is desired.

Dynamic generation of advertisement text

Distribution displays for categories are provided which illuminate the distribution of continuous attributes over all cases in a category, and which provide a histogram of the population of the different states of categorical attributes. An array of such displays by attribute (in one dimension) and category (in another dimension) may be provided. Category diagram displays are also provided for visualizing the different categories, and their distributions, populations, and similarities. These are displayed through different shading of nodes and edges representing categories and the relationship between two categories, and through proximity of nodes.

System and method for visualization of categories

The present web service platform includes a set of application program interfaces (APIs) and a framework for adding services that correspond to the APIs. The web service platform may also support a stored procedure (sproc) that allows combining results from two or more services before transmitting results to an application. The services relate to keyword technologies.

Web service platform for keyword technologies

The subject invention relates to systems and methods to extend the capabilities of declarative data modeling languages. In one aspect, a declarative data modeling language system is provided. The system includes a data modeling language component that generates one or more data mining models to extract predictive information from local or remote databases. A language extension component facilitates modeling capability in the data modeling language by providing a data sequence model or a time series model within the data modeling language to support various data mining applications.

Modeling sequence and time series data in predictive analytics

Systems and methods are provided for generating prediction queries to help a user build and execute prediction queries. A user interface (UI) is provided that is easy to use and understand in connection with the generation of a prediction query for data mining. The UI can be instantiated from a variety of disparate sources that may request query building services. While prediction queries and relational queries are quite different, the UI enables prediction queries to be built in a manner that is similar to the way relational queries are built. In one embodiment, the main screen of the UI includes four main components: (1) a table column mapping area, (3) a selection grid area, (4) a query text display area and (5) a query result grid area. In one embodiment, the query text display area and the query result grid area are initially not presented to the user.

Systems and methods for generating prediction queries

A language schema that integrates multidimensional extensions (e.g., MDX) and data mining extensions (e.g., DMX) for performing data mining operations on data residing in OLAP cubes. The schema provides that the &#x3c;source-data-query&#x3e; can not only be a relational query, rather a multidimensional query formed using MDX, for example. The operations of model creation, training and prediction are described.

Combining multidimensional expressions and data mining extensions to mine OLAP cubes

A standard mechanism for directly accessing unstructured data types (e.g., image, audio, video, gene sequencing and text data) in accordance with data mining operations is provided. The subject innovation can enable access to unstructured data directly from within the data mining engine or tool. Accordingly, the innovation enables multiple vendors to provide algorithms for mining unstructured data on a data mining platform (e.g., an SQL-brand server), thereby increasing adoption. As well, the subject innovation allows users to directly mine unstructured data that is not fixed-length, without pre-processing and tokenizing the data external to the data mining engine. In accordance therewith, the innovation can provide a mechanism to expand declarative language content types to include an 'unstructured' data type thereby enabling a user and/or application to affirmatively designate mining data as an unstructured type.

Unstructured data in a mining model language

Systems and methods that cleanse data in Extract, Transform, Load environments (ETL), via employing an outlier detect component that is positioned in data pipeline to data warehouse(s). Such outlier detect component employs a cluster mining model to split data into normal and outlier data. Different predictive models can be employed to detect outliers in different data slices to enhance the accuracy of the predictions. In addition, a graphical user interface (GUI) enables a user to interact with cluster groups that are created and/or analyzed by the outlier detect component.

Transform for outlier detection in extract, transfer, load environment

A system that facilitates data mining comprises a reception component that receives command(s) in a declarative language that relate to utilizing an output of a first data mining model as an input to a second data mining model. An implementation component analyzes the received command(s) and implements the command(s) with respect to the first and second data mining models. In another aspect of the subject invention, the reception component can receive further command(s) in a declarative language with respect to causing one or more of the first and second data mining models to output a prediction, the prediction desirably generated without prediction input, the implementation component causes the one or more of the first and second data mining models to output the prediction.

Systems and methods that facilitate data mining

The subject disclosure pertains to extensible data mining systems, means, and methodologies. For example, a data mining system is disclosed that supports plug-in or integration of non-native mining algorithms, perhaps provided by third parties, such that they function the same as built-in algorithms. Furthermore, non-native data mining viewers may also be seamlessly integrated into the system for displaying the results of one or more algorithms including those provided by third parties as well as those built-in. Still further yet, support is provided for extending data mining languages to include user-defined functions (UDFs).

Extensible data mining framework

Systems and methods are provided for producing a mining model accuracy display that depicts the model's accuracy at predicting a state for a multiple-state variable. The model predicts a state and provides an associated probability for each case. Points are graphed such that one coordinate of the data point corresponds to a number N of cases and the other coordinate corresponds to the number of correct predictions made in the top N cases by probability.

Systems and methods for mining model accuracy display for multiple state prediction

A drill-through feature is provided which provides a universal drill-through to mining model source data from a trained mining model. In order for a user or application to obtain model content information on a given node of a model, a universal function is provided whereby the user specifies the node for a model and data set, and the cases underlying that node for that model and data set are returned. A sampling of underlying cases may be provided, where only a sampling of the cases represented in the node is requested.

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Bellevue, WA, United States of America

Zhaohui Tang