Abstract: Disclosed is a technical solution to summarize a multimodal conferencing environment. The solution is designed to improve efficiency and accuracy of computing systems as a summarization tool by incorporating memory, machine readable instructions, and processor circuitry. The solution executes the functions of adjusting a language model based on a terminology utilized in a first context data; generating a conversation summary from a transcription and a human controlled variable; extracting a semantic entity from the conversation summary and second context data, where the second context data is indicative of an input associated with a conferencing environment; and summarize the semantic entity and the second context data using the adjusted language model.

Abstract: Systems and methods may provide for conducting an interest analysis of data associated with a user, wherein the interest analysis distinguishes between abstract interests and social interests. Additionally, one or more recommendations may be generated for the user based on the interest analysis and a current context of the user, wherein the one or more recommendations may be presented to the user. In one example, the abstract interests identify types of topics and types of objects, and the social interests identify types of social groups.

Abstract: Technologies for automated context-aware media curation include a computing device that captures context data associated with media objects. The context data may include location data, proximity data, behavior data of the user, and social activity data. The computing device generates inferred context data using one or more cognitive or machine learning algorithms. The inferred context data may include semantic time or location data, activity data, or sentiment data. The computing device updates a user context model and an expanded media object graph based on the context data and the inferred context data. The computing device selects one or more target media objects using the user context model and the expanded media object graph. The computing device may present context-aware media experiences to the user with the target media objects. Context-aware media experiences may include contextual semantic search and contextual media browsing. Other embodiments are described and claimed.

Abstract: Systems and methods may provide for conducting an interest analysis of data associated with a user, wherein the interest analysis distinguishes between abstract interests and social interests. Additionally, one or more recommendations may be generated for the user based on the interest analysis and a current context of the user, wherein the one or more recommendations may be presented to the user. In one example, the abstract interests identify types of topics and types of objects, and the social interests identify types of social groups.

Abstract: Embodiments utilize a framework for modeling user's social roles in online self-expression tools such as blog or social networking, via semantic modeling techniques. The different ways users engage with content when stating explicit interests in their profile and via social expressions in a community are modeled. Certain themes guide the patterns users follow for expressing their interests in this community. An embodiment allows users to track how their posts and comments reflect with their online behavior. An embodiment infers the needs of the online community and makes suggestions or recommendations or sends alerts to users. Other embodiments are described and claimed.

Abstract: Systems and methods may provide for conducting an interest analysis of data associated with a user, wherein the interest analysis distinguishes between abstract interests and social interests. Additionally, one or more recommendations may be generated for the user based on the interest analysis and a current context of the user, wherein the one or more recommendations may be presented to the user. In one example, the abstract interests identify types of topics and types of objects, and the social interests identify types of social groups.

Abstract: A mechanism is described for facilitating personal assistance for curation of multimedia and generation of stories at computing devices according to one embodiment. A method of embodiments, as described herein, includes receiving, by one or more capturing/sensing components at a computing device, one or more media items relating to an event, and capturing a theme from the one or more media items, where the theme is captured based on at least one of activities, textual content, and scenes associated with the event. The method may further include forming a plurality of story elements to generate a story relating to the event, where the plurality of story elements are formed based on at least one of one or more characters, the theme associated with the event, and one or more emotions associated with the one or more characters, wherein the story is presented, via one or more display devices, to one or more users having access to the one or more display devices.

Abstract: Technologies for automated context-aware media curation include a computing device that captures context data associated with media objects. The context data may include location data, proximity data, behavior data of the user, and social activity data. The computing device generates inferred context data using one or more cognitive or machine learning algorithms. The inferred context data may include semantic time or location data, activity data, or sentiment data. The computing device updates a user context model and an expanded media object graph based on the context data and the inferred context data. The computing device selects one or more target media objects using the user context model and the expanded media object graph. The computing device may present context-aware media experiences to the user with the target media objects. Context-aware media experiences may include contextual semantic search and contextual media browsing. Other embodiments are described and claimed.

Abstract: A mechanism is described for facilitating personal assistance for curation of multimedia and generation of stories at computing devices according to one embodiment. A method of embodiments, as described herein, includes receiving, by one or more capturing/sensing components at a computing device, one or more media items relating to an event, and capturing a theme from the one or more media items, where the theme is captured based on at least one of activities, textual content, and scenes associated with the event. The method may further include forming a plurality of story elements to generate a story relating to the event, where the plurality of story elements are formed based on at least one of one or more characters, the theme associated with the event, and one or more emotions associated with the one or more characters, wherein the story is presented, via one or more display devices, to one or more users having access to the one or more display devices.

Abstract: One embodiment provides an apparatus. The apparatus includes a processor; at least one peripheral device coupled to the processor; a memory coupled to the processor; a generic sentiment model and a first domain training corpus stored in memory; and a hybrid sentiment analyzer logic stored in memory and to execute on the processor. The hybrid sentiment analyzer logic includes a sentiment lexicon generator logic to generate a domain sentiment lexicon based, at least in part, on the first domain training corpus and to store the domain sentiment lexicon in memory, a lexicon-based sentiment classifier logic to generate an annotated training corpus unsupervisedly, based, at least in part, on the domain sentiment lexicon and to store the annotated training corpus in memory, and a model-based sentiment adaptor logic to adapt the generic sentiment model based, at least in part, on the annotated training corpus to generate an adapted sentiment model and to store the adapted sentiment model in memory.

Abstract: Systems and methods may provide for conducting an interest analysis of data associated with a user, wherein the interest analysis distinguishes between abstract interests and social interests. Additionally, one or more recommendations may be generated for the user based on the interest analysis and a current context of the user, wherein the one or more recommendations may be presented to the user. In one example, the abstract interests identify types of topics and types of objects, and the social interests identify types of social groups.

Abstract: Embodiments utilize a framework for modeling user's social roles in online self-expression tools such as blog or social networking, via semantic modeling techniques. The different ways users engage with content when stating explicit interests in their profile and via social expressions in a community are modeled. Certain themes guide the patterns users follow for expressing their interests in this community. An embodiment allows users to track how their posts and comments reflect with their online behavior. An embodiment infers the needs of the online community and makes suggestions or recommendations or sends alerts to users. Other embodiments are described and claimed.