Abstract: The disclosure herein describes generating an application from input content. Input content of a content type is obtained, such as an image file, digital document file, or the like. A content data extractor is selected from a set of content data extractors based on the content type. A set of content entities is extracted from the obtained input content using the selected content data extractor, such as text labels, text boxes, buttons, or the like. The set of content entities are normalized according to a standard interface schema and an application template is generated using the normalized set of content entities, whereby an application can be developed using the generated application template. The disclosure enables application interfaces to be designed using a variety of methods and for those different types of designs to be efficiently converted to a functional application.

Abstract: Examples described herein generate training data for machine learning (ML) for natural language (NL) processing (such as semantic parsing for translating NL). A formula tree is generated based on sampling both a formula grammar and NL templates. Using the formula tree, an ML training data instance pair is generated comprising a formula example and an NL example. A context example may also be used during instantiation of the formula tree. An ML model is trained with training data including the ML training data instance pair, and ML output is generated from NL input. The ML output includes, for example, a machine-interpretable formula, a database querying language command, or a general programming language instruction. Some examples support context-free grammar, probabilistic context-free grammar, and/or non-context-free production rules.

Abstract: The disclosure herein describes generating an application from input content. Input content of a content type is obtained, such as an image file, digital document file, or the like. A content data extractor is selected from a set of content data extractors based on the content type. A set of content entities is extracted from the obtained input content using the selected content data extractor, such as text labels, text boxes, buttons, or the like. The set of content entities are normalized according to a standard interface schema and an application template is generated using the normalized set of content entities, whereby an application can be developed using the generated application template. The disclosure enables application interfaces to be designed using a variety of methods and for those different types of designs to be efficiently converted to a functional application.

Abstract: The present invention extends to methods, systems, and computer program products for forming data responsive to a query. Responding to a query can include selecting data views on top of data sources. A data catalog stores data elements from different data sources and stores links between data elements from the different data sources. A view can be selected for a query based on one or more of: classification of data included in the data catalog or prior usage of data included in the data catalog. A selected data view is populated with data elements from the data catalog using the links to determine that data elements spanning multiple data sources satisfy the query. The data catalog can be used to identify relationships between data elements from different data sources that would not otherwise be identified.

Abstract: In one embodiment, datasets are stored in a catalog. The datasets are enriched by establishing relationships among the domains in different datasets. A user searches for relevant datasets by providing examples of the domains of interest. The system identifies datasets corresponding to the user-provided examples. The system them identifies connected subsets of the datasets that are directly linked or indirectly linked through other domains. The user provides known relationship examples to filter the connected subsets and to identify the connected subsets that are most relevant to the user's query. The selected connected subsets may be further analyzed by business intelligence/analytics to create pivot tables or to process the data.

Abstract: The present invention extends to methods, systems, and computer program products for forming data responsive to a query. Responding to a query can include selecting data views on top of data sources. A data catalog stores data elements from different data sources and stores links between data elements from the different data sources. A view can be selected for a query based on one or more of: classification of data included in the data catalog or prior usage of data included in the data catalog. A selected data view is populated with data elements from the data catalog using the links to determine that data elements spanning multiple data sources satisfy the query. The data catalog can be used to identify relationships between data elements from different data sources that would not otherwise be identified.

Abstract: The present invention extends to methods, systems, and computer program products for creating data views. Embodiments of the invention allow automatic creation of data views/projections on top of data sources. A view can be created on one data source (by looking at one or multiple data elements within the data source) or by looking at multiple data sources (of the same or different data types) and combining elements into a view. Data sources can be any kind of data source, including but not limited to: databases, files, and Web services. Views can be picked from a set of predefined views, picked from views of another tenant (either statically or using fuzzy logic), selected based on data element classifications and/or data element relationship classifications, selected based on data usage (e.g., by looking at logs), etc.

Abstract: Techniques and tools for encoding and decoding motion vector information for video images are described. For example, a video encoder yields an extended motion vector code by jointly coding, for a set of pixels, a switch code, motion vector information, and a terminal symbol indicating whether subsequent data is encoded for the set of pixels. In another aspect, an encoder/decoder selects motion vector predictors for macroblocks. In another aspect, a video encoder/decoder uses hybrid motion vector prediction. In another aspect, a video encoder/decoder signals a motion vector mode for a predicted image. In another aspect, a video decoder decodes a set of pixels by receiving an extended motion vector code, which reflects joint encoding of motion information together with intra/inter-coding information and a terminal symbol. The decoder determines whether subsequent data exists for the set of pixels based on e.g., the terminal symbol.

Abstract: The present invention extends to methods, systems, and computer program products for creating data views. Embodiments of the invention allow automatic creation of data views/projections on top of data sources. A view can be created on one data source (by looking at one or multiple data elements within the data source) or by looking at multiple data sources (of the same or different data types) and combining elements into a view. Data sources can be any kind of data source, including but not limited to: databases, files, and Web services. Views can be picked from a set of predefined views, picked from views of another tenant (either statically or using fuzzy logic), selected based on data element classifications and/or data element relationship classifications, selected based on data usage (e.g., by looking at logs), etc.

Abstract: In one embodiment, datasets are stored in a catalog. The datasets are enriched by establishing relationships among the domains in different datasets. A user searches for relevant datasets by providing examples of the domains of interest. The system identifies datasets corresponding to the user-provided examples. The system them identifies connected subsets of the datasets that are directly linked or indirectly linked through other domains. The user provides known relationship examples to filter the connected subsets and to identify the connected subsets that are most relevant to the user's query. The selected connected subsets may be further analyzed by business intelligence/analytics to create pivot tables or to process the data.

Abstract: In one embodiment, datasets are stored in a catalog. The datasets are enriched by establishing relationships among the domains in different datasets. A user searches for relevant datasets by providing examples of the domains of interest. The system identifies datasets corresponding to the user-provided examples. The system them identifies connected subsets of the datasets that are directly linked or indirectly linked through other domains. The user provides known relationship examples to filter the connected subsets and to identify the connected subsets that are most relevant to the user's query. The selected connected subsets may be further analyzed by business intelligence/analytics to create pivot tables or to process the data.

Abstract: Techniques and tools for encoding and decoding motion vector information for video images are described. For example, a video encoder yields an extended motion vector code by jointly coding, for a set of pixels, a switch code, motion vector information, and a terminal symbol indicating whether subsequent data is encoded for the set of pixels. In another aspect, an encoder/decoder selects motion vector predictors for macroblocks. In another aspect, a video encoder/decoder uses hybrid motion vector prediction. In another aspect, a video encoder/decoder signals a motion vector mode for a predicted image. In another aspect, a video decoder decodes a set of pixels by receiving an extended motion vector code, which reflects joint encoding of motion information together with intra/inter-coding information and a terminal symbol. The decoder determines whether subsequent data exists for the set of pixels based on e.g., the terminal symbol.

Abstract: A method includes receiving a concept hierarchy at a computing device. The concept hierarchy identifies concepts associated with a document corpus. An interface based on the concept hierarchy is generated. The interface is operable to navigate and search the concept hierarchy.

Abstract: Methods, systems, and computer program products are provided for deriving and updating document similarity indices for a plurality of documents. The number of maintained similarities can be controlled to conserve CPU and storage resources.

Abstract: A method includes receiving a concept hierarchy at a computing device. The concept hierarchy identifies concepts associated with a document corpus. An interface based on the concept hierarchy is generated. The interface is operable to navigate, search, and modify the concept hierarchy. The method includes transmitting the interface for display to a display device.

Abstract: Techniques and tools for encoding and decoding motion vector information for video images are described. For example, a video encoder yields an extended motion vector code by jointly coding, for a set of pixels, a switch code, motion vector information, and a terminal symbol indicating whether subsequent data is encoded for the set of pixels. In another aspect, an encoder/decoder selects motion vector predictors for macroblocks. In another aspect, a video encoder/decoder uses hybrid motion vector prediction. In another aspect, a video encoder/decoder signals a motion vector mode for a predicted image. In another aspect, a video decoder decodes a set of pixels by receiving an extended motion vector code, which reflects joint encoding of motion information together with intra/inter-coding information and a terminal symbol. The decoder determines whether subsequent data exists for the set of pixels based on e.g., the terminal symbol.

Abstract: Techniques and tools for encoding and decoding motion vector information for video images are described. For example, a video encoder yields an extended motion vector code by jointly coding, for a set of pixels, a switch code, motion vector information, and a terminal symbol indicating whether subsequent data is encoded for the set of pixels. In another aspect, an encoder/decoder selects motion vector predictors for macroblocks. In another aspect, a video encoder/decoder uses hybrid motion vector prediction. In another aspect, a video encoder/decoder signals a motion vector mode for a predicted image. In another aspect, a video decoder decodes a set of pixels by receiving an extended motion vector code, which reflects joint encoding of motion information together with intra/inter-coding information and a terminal symbol. The decoder determines whether subsequent data exists for the set of pixels based on e.g., the terminal symbol.

Abstract: Methods, systems, and computer program products are provided for deriving and updating document similarity indices for a plurality of documents. The number of maintained similarities can be controlled to conserve CPU and storage resources.

Abstract: In one embodiment, datasets are stored in a catalog. The datasets are enriched by establishing relationships among the domains in different datasets. A user searches for relevant datasets by providing examples of the domains of interest. The system identifies datasets corresponding to the user-provided examples. The system them identifies connected subsets of the datasets that are directly linked or indirectly linked through other domains. The user provides known relationship examples to filter the connected subsets and to identify the connected subsets that are most relevant to the user's query. The selected connected subsets may be further analyzed by business intelligence/analytics to create pivot tables or to process the data.

Abstract: Systems are used for identifying key phrases within documents. These systems utilize a tags and a tag index to determine what a document primarily relates to. For example, an integrated data flow and extract-transform-load pipeline, crawls, parses and word breaks large corpuses of documents in database tables. Documents can be broken into tuples. The tuples can be sent to a heuristically based algorithm that uses statistical language models and weight plus cross-entropy threshold functions to summarize the document into its “top N” most statistically significant phrases. These systems can scale efficiently (e.g., linearly) and (potentially large numbers of) documents can be characterized by salient and relevant key phrases (tags).