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Among sub-languages (i.e., subdivided categories of natural language), spatial language is the most important for human-robot interaction at various scenes in our daily life. This paper describes systematic analysis and synthesis of human subjective knowledge expressed in spatial language based on certain cognitive hypotheses of human mental image and gives a brief sketch of its implementation. Mental...
Standard models in bio-evolutionary game theory involve repetitions of a single stage game (e.g., the Prisoner's Dilemma or the Stag Hunt); but it is clear that repeatedly playing the {\em same} stage game is not an accurate model of most individuals' lives. Rather, individuals' interactions with others correspond to many different kinds of stage games. In this work, we concentrate on discovering...
Schema merging involves integration of multiple data sources into a global conceptual schema (GCS). It plays a significant role in different application domains, like multidatabase systems. A prerequisite to schema merging is schema matching, in which source databases are compared with each other to identify corresponding elements. There are different possibilities to create a GCS given a set of data...
One of the major issues of monitoring activities in smart environments is the building of activity models from sensor's timed data. This paper proposes a general theoretical approach to this aim that provides operational results as it is illustrated with the prototypical home of the GerHome project. This proposal is based on the use of a Knowledge Engineering methodology and a Machine Learning process...
With the rapid rise of ESP in China in recent years, it's imperative that we should look deeper into the cognitive mechanism of the curriculum. The article explores the relationship between cognitive linguistics and English learning in China and analyzes its implications on the practice of ESP curriculum, including course design, textbook compilation, and teaching personnel development, etc.
Emotion classification and retrieval in video is important in video analysis. It has great significance for the classification of video management and video retrieval. In this paper, we design an emotion classification and retrieval system for video based on user experience. We analyzed problems of the current emotion classification and retrieval algorithm. First we define the type of video classified...
The analysis of sets of degraded documents, like historical ones, is error-prone and requires human help to achieve acceptable quality levels. However, human interaction raises 3 main issues when processing important amounts of pages: none of the user or the system should wait for work, information provided by a human operator should not be restricted to local isolated corrections, but rather produce...
Bilingual semantic term association is very useful in cross-language information retrieval, statistical machine translation, and many other applications in natural language processing. In this paper, we present a method, named SBA-term, which applies sparse linear regression (Lasso, Least Squares with l1 penalty) and L2 rescaling for design matrix to the task of bilingual term association. The approach...
Using semantic techniques, we determined a probabilistic score indicating whether news stories were more optimistic (or solutions-oriented), versus their being more pessimistic (or threnodic). We observed over the length of our study that some news outlets, which were comparable in their topical coverage, quantity of output, and geographical focus, differed vastly in their level of optimistic or solutions-oriented...
The paper focuses on studying a new problem in enterprise data integration, i.e. attribute correspondences identification in multilingual schemas, and proposes a multilingual ontology-based method for the problem. In this paper, the problem is analyzed through comparing two schemas of a large financial corporate of China. And based on the multilingual ontology, attribute correspondences are identified...
Enterprise-scale information systems are deeply entwined with the networks of social practice that use and support them. Yet “interoperability” between information systems and social communities of practice is not always easily achieved, because these disparate types of entities operate according to different logics and respond differently to innovation processes. In this paper we identify differences...
we present the Scenario Markup Language (SML), a powerful language for authoring realistic traffic situations. This effort is part of a novel framework for automatically generating complex scenarios with static and dynamic elements. SML facilitates the scripting of behavioral driver studies in networked multi-user online three-dimensional (3D) virtual worlds.
Physical cooperation with humans greatly enhances the capabilities of robotic systems when leaving standardized industrial settings. Our novel cognition-enabled control framework presented in this paper enables a robotic assistant to enrich its own experience by acquisition of human task knowledge during joint manipulation. Our robot incrementally learns semantic task structures during joint task...
A theory for describing the systems engineering process using formal mathematical structures is presented in this paper. This abstraction of the systems engineering process makes it possible to concentrate on the operations and structures involved in the process without the distraction of the narrative word. An important aspect in the formulation of this theory is the inclusion of people as part of...
Can a high-performance document image recognition system be built without detailed knowledge of the application? Having benefited from the statistical machine learning revolution of the last twenty years, our architectures rely less on hand-crafted special-case rules and more on models trained on labeled-sample data sets. But urgent questions remain. When we can't collect (and label) enough real training...
Our research addresses the question as to whether automatically collected quantitative data about people's behavior online can be analyzed to spot patterns that indicate behaviors of interest. Based on ethnographic studies, we find that people, going about their routine work, exhibit patterns in terms of their routine online activities and work rhythms. Such patterns can be comprised of many diverse...
The communicative importance of gestures in teaching environments have been widely studied. Two classes of gestures — point and spread gestures — have been identified to indicate pedagogical importance in teaching discourse [1]. In this work, we propose a system for the identification of the poses of point and spread gestures as a preliminary step toward their identification in low-quality unstructured...
Based on WordNet, we do some research on the co-occurrence phenomena of semantic relations in objective knowledge system. According to the structural characteristics of semantic relations in objective knowledge system, a co-occurrence degree function for pairs of semantic relations was proposed. We calculate co-occurrence degree from the data obtained by making statistical tests. Some useful conclusions...
We address the discovery of typical activities in video stream contents and its exploitation for estimating the abnormality levels of these streams. Such estimates can be used to select the most interesting cameras to show to a human operator. Our contributions come from the following facets: i) the method is fully unsupervised and learns the activities from long term data; ii) the method is scalable...
The paper introduces a technique for grammar rules that licence post-and pre-modified phrases, by using a generalized approach to constraint based lexicalized grammar. The rules generate iterative modification by avoiding spurious syntactic ambiguity. The rules of syntactic modification are lexically restricted by the lexical head of the modifier expression via a grammatical feature and its value.
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