Twine

Twine services information storage, authoring and discovery through its website and browser-based tools. The service, intended for regular web users, attempts to automate certain processes related to data categorization and keyword-association (tagging)[4]. The system employs natural language processing and machine learning to extract concepts from written text in user data[1] and express it using RDF triples tied to a semantic taxonomy based on concepts mined from Wikipedia[4]. This makes it easier for machines to process the data[5][6]. The extracted data is useful to search on the website where, in comparison to a non-semantic keyword categorization scheme, a user can additionally select a type of thing he wants to find such as person or location.

Twine is a social network and its users can add contacts, send private messages and share information. Users can collaborate on collecting data through private or public twines; data collections focused on a certain topic, such as politics[7].

Data can be imported to Twine's website through conventional uploading of files, writing text with a WYSIWYG editor or using a bookmarking tool for webpages. The tool works in a similar manner as other social bookmarking websites. Users can manually write summaries, specify keywords (tags) and select an image to include in the bookmark that appears on Twine's website. Certain types of media in bookmarks, such as YouTube videos, are automatically embedded in Twine's pages when bookmarked. Twine also offers limited wiki capabilities to collaboratively edit documents.

Information discovery is mostly done through a user's main page where items appear, organized by the twine they belong to. Twine also uses machine learning technologies that, over time, use semantic metadata to learn and generate more relevant, automatic information recommendations of possible interest to the user.