Visual Representation of Text in Web Documents and Its Interpretation

This paper examines the uses of text and its representation on Web documents in terms of the challenges in its interpretation. Particular attention is paid to the significant problem of non-uniform representation of text. This non-uniformity is mainly due to the presence of semantically important text in image form as opposed to the standard encoded text. The issues surrounding text representation in Web documents are discussed in the context of colour perception and spatial representation. The characteristics of the representation of text in image form are examined and research towards interpreting these images of text is briefly described

Visual Representation of Text in Web Documents and Its Interpretation

This paper examines the uses of text and its representation on Web documents in terms of the challenges in its interpretation. Particular attention is paid to the significant problem of non-uniform representation of text. This non-uniformity is mainly due to the presence of semantically important text in image form as opposed to the standard encoded text. The issues surrounding text representation in Web documents are discussed in the context of colour perception and spatial representation. The characteristics of the representation of text in image form are examined and research towards interpreting these images of text is briefly described

The cat's cradle network

In this paper we will argue that the representation of context in knowledge management is appropriately served by the representation of the knowledge networks in an historicised form. Characterising context as essentially extra to any particular knowledge representation, we argue that another dimension to these be modelled, rather than simply elaborating a form in its own terms. We present the formalism of the cat's cradle network, and show how it can be represented by an extension of the Pathfinder associative network that includes this temporal dimension, and allows evolutions of understandings to be traced. Grounding its semantics in communities of practice ensures utility and cohesiveness, which is lost when mere externalities of a representation are communicated in fully fledged forms. The scheme is general and subsumes other formalisms for knowledge representation. The cat's cradle network enables us to model such community-based social constructs as pattern languages, shared memory and patterns of trust and reliance, by placing their establishment in a structure that shows their essential temporality

Context guided retrieval

This paper presents a hierarchical case representation that uses a context guided retrieval method The performance of this method is compared to that of a simple flat file representation using standard nearest neighbour retrieval. The data presented in this paper is more extensive than that presented in an earlier paper by the same authors. The estimation of the construction costs of light industrial warehouse buildings is used as the test domain. Each case in the system comprises approximately 400 features. These are structured into a hierarchical case representation that holds more general contextual features at its top and specific building elements at its leaves. A modified nearest neighbour retrieval algorithm is used that is guided by contextual similarity. Problems are decomposed into sub-problems and solutions recomposed into a final solution. The comparative results show that the context guided retrieval method using the hierarchical case representation is significantly more accurate than the simpler flat file representation and standard nearest neighbour retrieval

Ontology-Based Context-Aware Service Discovery for Pervasive Environments

Existing service discovery protocols use a service matching process in order to offer services of interest to the clients. Potentially, the context information of the services and client can be used to improve the quality of service matching. To make use of context information in service matching, service discovery needs to address certain challenges. Firstly, it is required that the context information should have unambiguous representation. Secondly, the mobile devices should be able to disseminate context information seamlessly in the fixed network. And thirdly, dynamic nature of the context information should be taken into account. The proposed Context Aware Service Discovery (CASD) architecture deals with these challenges by means of an ontological representation and processing of context information, a concept of nomadic mobile context source and a mechanism of persistent service discovery respectively. This paper discusses proposed CASD architecture, its implementation and suggests further enhancements

Crossmodal content binding in information-processing architectures

Operating in a physical context, an intelligent robot faces two fundamental problems. First, it needs to combine information from its different sensors to form a representation of the environment that is more complete than any of its sensors on its own could provide. Second, it needs to combine high-level representations (such as those for planning and dialogue) with its sensory information, to ensure that the interpretations of these symbolic representations are grounded in the situated context. Previous approaches to this problem have used techniques such as (low-level) information fusion, ontological reasoning, and (high-level) concept learning. This paper presents a framework in which these, and other approaches, can be combined to form a shared representation of the current state of the robot in relation to its environment and other agents. Preliminary results from an implemented system are presented to illustrate how the framework supports behaviours commonly required of an intelligent robot