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Filaments of Meaning in Word Space: Advances in Information Retrieval (2008), pp. 531-538.Word space models, in the sense of vector space models built on distributional data taken from texts, are used to model semantic relations between words. We argue that the high dimensionality of typical vector space models lead to unintuitive effects on modeling likeness of meaning and that the local structure of word spaces is where interesting semantic relations reside. We show that the local structure of word spaces has substantially different dimensionality and character than the global space and that this structure shows potential to be exploited for further semantic analysis using methods for local analysis of vector space structure rather than globally scoped methods typically in use today such as singular value decomposition or principal component analysis.Jussi Karlgren, Anders Holst, Magnus Sahlgren

Source: Advances in Information Retrieval (2008), pp. 531-538.
The two cultures: mashing up web 2.0 and the semantic web: (2007), pp. 825-834.Anupri ya Ankolekar, Markus Kr&\#246;t zsch, Thanh Tran, Denny Vrandecic

Source: (2007), pp. 825-834.
P-TAG: large scale automatic generation of personalized annotation tags for the web: (2007), pp. 845-854.Paul, Stefania Costache, Wolfgang Nejdl, Siegfried Handschuh

Source: (2007), pp. 845-854.
Semantic Structuring of and Information Extraction from Medical Documents Using the UMLS.: Methods of information in medicine, Vol. 47, No. 5. (2008), pp. 425-434.OBJECT IVES: This paper introduces SeReMeD (Semantic Representation of Medical Documents), a method for automatically generating knowledge representation s from natural language documents. The suitability of the Unified Medical Language System (UMLS) as domain knowledge for this method is analyzed. METHODS: SeReMeD combines existing language engineering methods and semantic transformation rules for mapping syntactic information to semantic roles. In this way, the relevant content of medical documents is mapped to semantic structures. In order to extract specific data, these semantic structures are searched for concepts and semantic roles. A study is carried out that uses SeReMeD to detect specific data in medical narratives such as documented diagnoses or procedures. RESULTS: The system is tested on chest X-ray reports. In first evaluations of the system's performance, the generation of semantic structures achieves a correctness of 80%, whereas the extraction of documented findings obtains values of 93% precision and 83% recall. CONCLUSIONS: The results suggest that the methods described here can be used to accurately extract data from medical narratives, although there is also some potential for improving the results. The proposed methods provide two main benefits. By using existing language engineering methods, the effort required to construct a medical information extraction system is reduced. It is also possible to change the domain knowledge and therefore to create a more (or less) specialized system, capable of handling various medical sub-domains.K Denecke

Source: Methods of information in medicine, Vol. 47, No. 5. (2008), pp. 425-434.
A semantically annotated corpus from MEDLINE abstracts: (1999)This paper outlines the features of this corpus.T Ohta, Y Tateishi, N Collier, C Nobata, K Ibushi, J Tsujii

Source: (1999)
A Unified Semantics Space Model: Location- and Context-Awaren ess (2007), pp. 103-120.Locati on-aware systems provide customised services or applications according to users? locations. While much research has been carried out in developing models to represent location information and spatial relationships, it is usually limited to modelling simple environments (cf. [13,19,3]). This paper proposes a unified space model for more complex environments (e.g., city plan or forest). This space model provides a flexible, expressive, and powerful spatial representation . It also proposes a new data structure ? an integrated lattice and graph model ? to express comprehensive spatial relationships. This structure not only provides multiple graphs at different abstraction levels, but it also collapses the whole map into smaller local graphs. This mechanism is beneficial in reducing the complexity of creating and maintaining a map and improving the efficiency of path finding algorithms.Jua n Ye, Lorcan Coyle, Simon Dobson, Paddy Nixon

Source: Location- and Context-Awareness (2007), pp. 103-120.
Semantic location modeling for location navigation in mobile environment: Mobile Data Management, 2004. Proceedings. 2004 IEEE International Conference on (2004), pp. 52-61.Location -based applications require a well-formed representation of spatial knowledge. Current location models can be classified into symbolic or geometric models. The former attempts to represent logical entities and their semantics, but requires a large amount of manual effort for describing them. On the other hand, the latter represents the geometric coordinates but not the semantics. In this paper, we present a semantic location model which preserves topology and distance semantics to support location navigation but at the same time facilitates programmatic model construction and maintenance. The model is based on a sound location theory. It is mainly composed of two hierarchies: a location hierarchy and an exit hierarchy, which can be derived from spatial maps, such as floor plans, without manual intervention. Through a series of model construction algorithms and a real example, we show that our model is simple but powerful enough to capture spatial connectivity and hierarchical relationship to support location-based applications. Furthermore, the location and exit hierarchies are easy to understand by human users.Haibo Hu, Dik-Lun Lee

Source: Mobile Data Management, 2004. Proceedings. 2004 IEEE International Conference on (2004), pp. 52-61.
Towards a Semantic Spatial Model for Pedestrian Indoor Navigation: Advances in Conceptual Modeling ? Foundations and Applications (2007), pp. 328-337.This paper presents a graph-based spatial model which can serve as a reference for guiding pedestrians inside buildings. We describe a systematic approach to construct the model from geometric data. In excess of the well-known topological relations, the model accounts for two important aspects of pedestrian navigation: firstly, visibility within spatial areas and, secondly, generating route descriptions. An algorithm is proposed which partitions spatial regions according to visibility criteria. It can handle simple polygons as encountered in floor plans. The model is structured hierarchically - each of its elements corresponds to a certain domain concept (?room?, ?door?, ?floor? etc.) and can be annotated with meta information. This is useful for applications in which such information have to be evaluated.Edga r-Philipp Stoffel, Bernhard Lorenz, Hans Ohlbach

Source: Advances in Conceptual Modeling ? Foundations and Applications (2007), pp. 328-337.
Ontology learning for the Semantic Web: IEEE Intelligent Systems and Their Applications, Vol. 16, No. 2. (2001), pp. 72-79.The Semantic Web relies heavily on formal ontologies to structure data for comprehensive and transportable machine understanding. Thus, the proliferation of ontologies factors largely in the Semantic Web's success. The authors present an ontology learning framework that extends typical ontology engineering environments by using semiautomatic ontology construction tools. The framework encompasses ontology import, extraction, pruning, refinement and evaluation.A Maedche, S Staab

Source: IEEE Intelligent Systems and Their Applications, Vol. 16, No. 2. (2001), pp. 72-79.
Towards Semantic Web Engineering:: The existence of semantically tagged Web pages is crucial to bring the Semantic Web to life. But it is still costly to develop and maintain Web applications that o#er data and meta-data. Several standard Web engineering methodologies exist for designing and implementing Web applications. In this paper we introduce a technique to extend existing Web engineering techniques to develop semantically tagged Web applications. The novelty of this technique is the definition and implementation of a...Weesa Xml

If you would like to find additional social bookmark based links on the topic of semantic we recommend the Open Tag Directory > Semantic. If you would like to find related tags we recommend Tag Patterns > Semantic.