| URL | Description |
|---|---|
| Google wants to rank websites based on facts not links | |
| Google's fact-checking bots build vast knowledge bank | |
| Harvesting Knowledge from Web Data and Text | Can we systematically harvest facts from the Web and compile them into a comprehensive machine-readable knowledge base? |
| In-Q-Tel | |
| Knowledge Integration Map | |
| Lab41 | |
| Ontology Language | In computer science and artificial intelligence, ontology languages are formal languages used to construct ontologies. They allow the encoding of knowledge about specific domains and often include reasoning rules that support the processing of that knowledge. Ontology languages are usually declarative languages, are almost always generalizations of frame languages, and are commonly based on either first-order logic or on description logic. |
| Semantics Discovery via Human Computation Games | The effective acquisition of (semantic) metadata is crucial for many present day applications. Games with a purpose address this issue by transforming computational problems into computer games. The authors present a novel approach to metadata acquisition via Little Search Game (LSG) – a competitive web search game, whose purpose is the creation of a term relationship network. From a player perspective, the goal is to reduce the number of search results returned for a given search term by adding negative search terms to a query. The authors describe specific aspects of the game’s design, including player motivation and anti-cheating issues. The authors have performed a series of experiments with Little Search Game, acquired real-world player input, gathered qualitative feedback from the players, constructed and evaluated term relationship network from the game logs and examined the types of created relationships. |
| Simulating a Global Brain |