Abstract: A request for a digital license associated with a software product is received from a device. The request includes a user ID of a user of the device, with the digital license having been generated in response to a request to activate the software product with a product key. A check is made as to whether a digital license bound to the user ID is available, and also whether the digital license can be returned to the device in accordance with the terms of the digital license. The digital license is returned if the digital license can be returned to the device in accordance with the terms (regardless of whether the device is a same device from which the product key was activated), and otherwise is not returned. The digital license can be removed from the device in accordance with the terms of the digital license.

Abstract: Aspects of the present disclosure identify social media conversational signals and deliver prospects of potential opportunities to conduct a sale in an automated fashion. Individuals, or groups of people, are identified who are in decision making mode, and the communications are presented to businesses and/or organizations to help complete the transaction. Unlike social listening platforms, which use keyword matching and sentiment analysis, in some embodiments this platform leverages machine learning (ML), natural language processing (NLP) and the Universal Human Relevance System (UHRS) to identity relevant results by classifying them into a domain specific taxonomy. These transactional events may be defined by the date and time stamp, what the potential customer is looking for, the time-frame for consideration of the purchase, and the geographic location of the individual at the time of the signal's publication. In addition, these transactional events can be customized to suit the context of a domain.

Abstract: Example methods, apparatuses, and systems (e.g., machines) are presented for a natural language classification engine or platform capable of processing configurable classification criteria in real time or near real time. While typical classification engines tend to require specific training for each domain to be classified for a subscriber, the classification engine of the present disclosure is capable of analyzing a single corpus of human communications and providing only the relevant messages or documents according to criteria generated on the fly by a subscriber. The classification engine of the present disclosure need not know beforehand what type of content is desired by the subscriber. In this way, the criteria specified by a subscriber can change dynamically, and the classification engine of the present disclosure may be capable of evaluating the criteria and then provide relevant documents or messages according to the changed criteria, without needing additional corpus training.

Abstract: Examples are presented for a classification system that utilizes multiple classification models to adapt to any desired set of raw data to be classified. The classification system may include multiple classification models stored in a model repository. A truth set of the raw data may be used to evaluate the fitness of each of the stored classification models. The models may be scored and ranked to determine which is the most appropriate to use for real time classification of the raw data. The optimal classification model may be used in a classification engine to classify the raw data in real time. This generates a classified output that may be interacted with by a user. A user interface may be used to permit feedback of the classified output to be generated. This feedback may then be transmitted to the offline system and recorded to further improve the classification models.

Abstract: Example methods, apparatuses, and systems (e.g., machines) are presented for an auction platform that determines winning bids for high value digital message content using a multi-tiered share-rank system. The auction platform allows for subscribers to bid for merely a share of a set of high value digital message content. Multiple other subscribers may also bid for the same share amount of the set of high value digital message content. The collective bids of multiple subscribers that equals the entire set of the high value digital message content is then compared against other subscribers who have formed collective bids by different sized shares.

Abstract: A request for a digital license associated with a software product is received from a device. The request includes a user ID of a user of the device, with the digital license having been generated in response to a request to activate the software product with a product key. A check is made as to whether a digital license bound to the user ID is available, and also whether the digital license can be returned to the device in accordance with the terms of the digital license. The digital license is returned if the digital license can be returned to the device in accordance with the terms (regardless of whether the device is a same device from which the product key was activated), and otherwise is not returned. The digital license can be removed from the device in accordance with the terms of the digital license.

Abstract: The present disclosure describes a meta-application framework that enables data to be associated with a class of applications called a meta-application. A meta-application entity may store attributes in common across multiple platforms. A platform entity may store attributes in common across multiple devices and/or operating systems. A device entity may be comprised by a particular set of hardware features and an operating system entity may be comprised of a particular set of software feature. Data associated with the meta-application framework may be accessed directly via data manipulation operations or alternatively by application operations via an application programming interface or via the aforementioned data manipulation operations. Applications may then identify application specific behavior at the appropriate level of detail.

Abstract: A request for a digital license associated with a software product is received from a device. The request includes a user ID of a user of the device, with the digital license having been generated in response to a request to activate the software product with a product key. A check is made as to whether a digital license bound to the user ID is available, and also whether the digital license can be returned to the device in accordance with the terms of the digital license. The digital license is returned if the digital license can be returned to the device in accordance with the terms (regardless of whether the device is a same device from which the product key was activated), and otherwise is not returned. The digital license can be removed from the device in accordance with the terms of the digital license.

Abstract: Search result re-ranking is provided by employing a concept graph from a metabase. When a search query is received, a query context of the search query is analyzed to identify dominant concepts for the search query. The dominant concepts are expanded by identifying the dominant concepts within a concept graph and identifying additional concepts having a strong relationship with the dominant concepts within the concept graph. A set of search results for the search query is analyzed to determine strength of relationship of each search result to the expanded concepts. The search results are re-ranked based on the strength of relationship of each search result to the expanded concepts and the strength of relationship of each expanded concept to the dominant concepts.

Abstract: A procedural inference system is described herein that infers procedural knowledge from various data sources to help a user complete one or more tasks for which the data sources provide information. The system understands users' queries, identifies a task at hand, provides recommendations on the steps to take and the agents to use based on a knowledge base of tasks and agents, and provides the fabric to determine which different agents can work together to help the user accomplish a task. Tasks can be started on one device and completed on another seamlessly. Users are able to finish complex, multi-step tasks efficiently, without trial and error or data reentry. Thus, the procedural inference system provides a generalized framework that helps users to complete tasks using already available data and does not ask each data provider to invest in infrastructure to build dedicated task information systems.

Abstract: Systems, methods, and computer-storage media for generating lateral concepts are provided. The system includes a search engine to receive user queries, a storage to store content and its associated categories, and a lateral concept generator. The lateral concept generator is connected to both the search engine and storage. The lateral concept generator selects lateral concepts from categories associated with the content based on similarity scores for the stored content.

Abstract: Systems, methods, and computer-storage media for generating lateral concepts are provided. The system includes a search engine to receive user queries, a storage to store content and its associated categories, and a lateral concept generator. The lateral concept generator is connected to both the search engine and storage. The lateral concept generator selects lateral concepts from categories associated with the content based on similarity scores for the stored content.

Abstract: Systems, methods, and computer-storage media for generating lateral concepts are provided. The system includes a search engine to receive user queries, a storage to store content and its associated categories, and a lateral concept generator. The lateral concept generator is connected to both the search engine and storage. The lateral concept generator selects lateral concepts from categories associated with the content based on similarity scores for the stored content.

Abstract: An application sequence may be composed in response to a user query. The application sequence may be based upon user data accessed by the application concierge service. Each application within the personalized chain of applications may request and receive data from the application concierge service about the other applications within the chain.

Abstract: Review and filtering of search results is facilitated by providing additional types of results beyond links to existing documents can be provided in addition to or in place of links to existing documents. These additional results can facilitate modifying a search request to filter out unwanted documents. The additional results, when in the form of content display objects and/or application display objects, can also provide the user with varying levels of information detail. In some preferred embodiments, an ontology based knowledge base can be leveraged in order to facilitate providing and filtering the results.

Abstract: A procedural inference system is described herein that infers procedural knowledge from various data sources to help a user complete one or more tasks for which the data sources provide information. The system understands users' queries, identifies a task at hand, provides recommendations on the steps to take and the agents to use based on a knowledge base of tasks and agents, and provides the fabric to determine which different agents can work together to help the user accomplish a task. Tasks can be started on one device and completed on another seamlessly. Users are able to finish complex, multi-step tasks efficiently, without trial and error or data reentry. Thus, the procedural inference system provides a generalized framework that helps users to complete tasks using already available data and does not ask each data provider to invest in infrastructure to build dedicated task information systems.

Abstract: An entity ranking system is described herein that provides an input signal of ranked attributes between a data source and an entity viewing application. By providing an input signal of ranked attributes the data source can influence the manner in which these applications consume the properties and relationships of these entities. This allows presentation of new information in a “most relevant first” manner and provides a cut-off point in cases of limited space. The system looks across the spectrum of property types and values for a given entity type, identifies the diversity of each attribute/value, and computes a rank based on multiple distance measures. Thus, the system provides ranking information from a data source to describe how to rank entity properties so that applications can be written more generically to deal with many types of entities while still displaying the most relevant entity information.

Abstract: Electronic documents are analyzed to identify assertions, which are inverted to generate questions that may be answered by the assertions. A document or a corpus of electronic documents may be analyzed to identify entities and relationships among entities within the text of the document(s). Assertions are identified based on the entities and relationships among the entities. Each assertion represents a fact about an entity, and a group of assertions represents a summary of the document or document corpus. The assertions are inverted to generate questions that may be answered by the assertions. The questions may be further analyzed to identify relevant concepts and topics and to cluster the questions around the concepts and topics. A combined graph may also be generated that facilitates traversal among topics, concepts, questions, assertions, document summaries, and documents.

Abstract: A table of contents is generated for search results in response to a search query by identifying semantic concepts as topics for inclusion within the table of contents. When a search query is received, a search is performed to identify search results. The search results are compared to an ontology of topics to identify relevant topics. Additionally, search results are compared to an ontology of partial topics to identify relevant partial topics, which are named. Independent key-phrases are further generated from search results and identified as key-phrase topics. The identified topics, named partial topics, and key-phrase topics are ranked, and topics are selected for inclusion within a table of contents. A search results page is returned in response to the search query that includes search results and the generated table of contents.

Abstract: Advertisements are selected for presentation on search result pages and web pages based on phrases generated from lateral concepts and topics identified for the search result pages and web pages. A search query or an indication of a web page is received for which advertisements are to be provided. Lateral concepts and topics are identified based on the search query or content of the web page. The lateral concepts and topics are used as phrases for selecting advertisements from an advertisement inventory. Selected advertisements are provided for presentation on a search results page in response to a search query or on a web page initially identified.