A method is provided to predict a value for a particular characteristic of a particular user of network-based services. A plurality of other users, other than the particular user, is determined, wherein the particular user has social ties to the plurality of other users. The social ties may be discerned, for example, by examining connections provided by the network-based service. In some examples, the social ties may be inferred by other methods as well. A value is predicted for the particular characteristic of the particular user based on values associated with the particular characteristic of the other users, with whom the particular user is determined to have the social ties. The predicted value for the particular characteristic of the particular user is monetized, such as by selling advertising to be caused to be displayed to at least the particular user. For example, requested compensation for the advertising is determined based at least in part on the predicted value for the particular characteristic of the particular user.
The present invention relates to a messenger system adapted to support the creation and publication of podcast episodes (either audio or video) from communications made via the messenger system. The messenger system may be entirely server-based, may require the use of limited client side software or may be entirely client based. The messenger system allows a user to select that a call be recorded for later use causing the messenger software to store the various audio and any video streams provided from each party to the call. A user interface is then provided that allows the user, after the call, to edit, combine, modify, or add to the different audio and video streams as desired to create a single media file containing audio or audiovisual data. This media file may then be published as an episode to a podcast.
Computer systems and methods incorporate user annotations (metadata) regarding various pages or sites, including annotations by a querying user and by members of a trust network defined for the querying user into search and browsing of a corpus such as the World Wide Web. A trust network is defined for each user, and annotations by any member of the querying user's trust network are made visible to the querying user during search and/or browsing of the corpus if the querying user and trust network members use similar queries to identify documents in the corpus. Users can also limit searches to content annotated by members of their trust networks or by members of a community selected by the user.
Architecture for targeted advertising using offline user behavior information. Information relating to offline behavior can be collected from cell phones, geolocation systems, credit card information, restaurants, grocery stores, etc., and this information is aggregated and employed in connection with selecting and displaying targeted advertising to a user when online. Machine learning and reasoning can be employed to make inferences and dynamically tune advertisement processing. Offline user information can also be employed to enhance context-based searching when the user goes online. The ranking of search results and content for display can be modified as a function of offline behavior. A system is provided that facilitates online advertising based on at least offline activity using a profile component for aggregating offline behavior information of a user and generating a related user profile. An advertising component employs the user profile in connection with delivery of an advertisement to the user when online.
A family of resources to help information workers be more effective, raise the value of information in their organisations and contribute to success. Read more »
Recently I have found myself cooing over visualisation maps (and heat maps) of health and well being resources. The content rich data is overlayed with mapping technologies, and some interesting themes and patterns are emerging.
A lot of the talk around social media in the last year has been around information overload. Social media has provided us with new and exciting ways to create content. But it has also meant learning new ways to manage and engage with social media tools. Are we teetering on the edge of an information overload precipice?
Information overload is a figment of your imagination. Or a failure of your filter. Or a symptom of your technological submissiveness. Depends on who you ask.
What if you had to sort through 3.5 million articles and social media posts a day and try to pull out the most relevant items for your organisation? What if you then had to cobble it all together into something readable for your top groups and executives in your organisation?
Alacra Compliance saves time by aggregating information from both free and fee-based sources and enabling users to conduct an accurate federated search across these sources (coined “simultaneous search” by Alacra).
FreePint Family
Quilting big data threads
The fallacy of information overload
Information overload: fact, fantasy or filter failure? 
