LANGUAGE COMPUTER CORPORATION

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The goal of this Direct to Phase II effort is to develop a prototype system for Cross-Lingual Unsupervised Extraction (CLUE) that can extract relevant information from across a variety of sources, mod ...

Language Computer Corporation’s (LCC) Lorify Knowledge Base organizes information from a large quantity of unstructured textual documents to facilitate easy analysis of the information. Usually ...

In Phase II of PLATO, we will develop a prototype plan and goal identification system that employs a rich model of domain actions and events, extracted automatically from a massive amount of real-worl ...

In Phase II of AQUIRE, we will develop a prototype document background generation and management system that can be used by analysts and decision makers to access information gathered from a wide vari ...

A significant challenge in extracting event attributes from unstructured text is that events possess a wide array of attributes which affect decision making. In a single document, an author may descri ...

In Phase II of PLATO, we will develop a prototype plan and goal identification system that employs a rich model of domain actions and events, extracted automatically from a massive amount of real-worl ...

In Phase I of PLATO (Plan Learning Across Textual Observations ), Language Computer Corporation will explore how best to migrate state-of-the-art plan recognition techniques to the more complex genre ...

In Phase II of KEPLER, we will develop a prototype Knowledge Base (KB) expansion system that employs rich common-sense knowledge resources to perform high-quality scalable inference over a KB. The sys ...

In Phase II of JOLTER, we will develop several extensions and improvements upon the probabilistic graphical models developed in Phase I for discovering topics, entities, and relations jointly. The sy ...