Abstract: An adaptable climate control method for controlling a thermal climate within a confined space based on thermal and/or physiological features of one or more occupants of the confined space is provided. The method includes receiving thermal images of a plurality of target areas from the occupants, identifying a plurality of interesting points of the received thermal images, and isolating the interesting points to construct thermal maps of the target areas. Thermal features of the occupants are determined using the respective thermal maps and the thermal features are used to construct thermal feature vectors for the occupants. Physiological features from physiological sensors can also be added as elements of the thermal feature vectors to form integrated vectors. The thermal feature vectors and/or integrated vectors are classified using a classifiers and at least a portion of the thermal climate of the confined space is adjusted based on the classification of the vectors.

Abstract: Systems and methods for processing natural language text using a graph obtain a natural language text and a query text, and parse that the natural language text into the plurality of text units, associating each with a graph node, and removing information leak text units from the plurality of text units. Connecting relationship between at least two of the remaining set of the plurality of text units are determined and associated with a graph edge between graph nodes. Based on the probabilistic relations between each graph node and the query text, graph node restart probabilities are determined for one or more of the graph nodes. The graph nodes that can be ranked.

Abstract: An adaptable climate control method for controlling a thermal climate within a confined space based on thermal and/or physiological features of one or more occupants of the confined space is provided. The method includes receiving thermal images of a plurality of target areas from the occupants, identifying a plurality of interesting points of the received thermal images, and isolating the interesting points to construct thermal maps of the target areas. Thermal features of the occupants are determined using the respective thermal maps and the thermal features are used to construct thermal feature vectors for the occupants. Physiological features from physiological sensors can also be added as elements of the thermal feature vectors to form integrated vectors. The thermal feature vectors and/or integrated vectors are classified using a classifiers and at least a portion of the thermal climate of the confined space is adjusted based on the classification of the vectors.

Abstract: The present invention provides a method and a system for automatic keyword extraction based on supervised or unsupervised machine learning techniques. Novel linguistically-motivated machine learning features are introduced, including discourse comprehension features based on construction integration theory, numeric features making use of syntactic part-of-speech patterns, and probabilistic features based on analysis of online encyclopedia annotations. The improved keyword extraction methods are combined with word sense disambiguation into a system for automatically generating annotations to enrich text with links to encyclopedic knowledge.

Abstract: The present invention provides a method of processing at least one natural language text using a graph. The method includes determining a plurality of text units based upon the natural language text, associating the plurality of text units with a plurality of graph nodes, and determining at least one connecting relation between at least two of the plurality of text units. The method also includes associating the at least one connecting relation with at least one graph edge connecting at least two of the plurality of graph nodes and determining a plurality of rankings associated with the plurality of graph nodes based upon the at least one graph edge. The method can also include a graphical visualization of at least one important text unit in a natural language text or collection of texts. Methods for word sense disambiguation, keyword extraction, and sentence extraction are also provided.

Abstract: The present invention provides a method and a system for automatic keyword extraction based on supervised or unsupervised machine learning techniques. Novel linguistically-motivated machine learning features are introduced, including discourse comprehension features based on construction integration theory, numeric features making use of syntactic part-of-speech patterns, and probabilistic features based on analysis of online encyclopedia annotations. The improved keyword extraction methods are combined with word sense disambiguation into a system for automatically generating annotations to enrich text with links to encyclopedic knowledge.

Abstract: The present invention provides a method of processing at least one natural language text using a graph. The method includes determining a plurality of text units based upon the natural language text, associating the plurality of text units with a plurality of graph nodes, and determining at least one connecting relation between at least two of the plurality of text units. The method also includes associating the at least one connecting relation with at least one graph edge connecting at least two of the plurality of graph nodes and determining a plurality of rankings associated with the plurality of graph nodes based upon the at least one graph edge. The method can also include a graphical visualization of at least one important text unit in a natural language text or collection of texts. Methods for word sense disambiguation, keyword extraction, and sentence extraction are also provided.