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1.
Human interactions with geographical information are contextualized by problem-solving activities which endow meaning to geospatial
data and processing. However, existing spatial data models have not taken this aspect of semantics into account. This paper
extends spatial data semantics to include not only the contents and schemas, but also the contexts of their use. We specify
such a semantic model in terms of three related components: activity-centric context representation, contextualized ontology
space, and context mediated semantic exchange. Contextualization of spatial data semantics allows the same underlying data
to take multiple semantic forms, and disambiguate spatial concepts based on localized contexts. We demonstrate how such a
semantic model supports contextualized interpretation of vague spatial concepts during human–GIS interactions. We employ conversational
dialogue as the mechanism to perform collaborative diagnosis of context and to coordinate sharing of meaning across agents
and data sources.
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2.
This paper describes a multi-modal corpus of hand-annotated meeting dialogues that was designed for studying addressing behaviour in face-to-face conversations. The corpus contains annotated dialogue acts, addressees, adjacency pairs and gaze direction. First, we describe the corpus design where we present the meetings collection, annotation scheme and annotation tools. Then, we present the analysis of the reproducibility and stability of the annotation scheme. 相似文献
3.
In this paper we present a framework for unified, personalized access to heterogeneous multimedia content in distributed repositories.
Focusing on semantic analysis of multimedia documents, metadata, user queries and user profiles, it contributes to the bridging
of the gap between the semantic nature of user queries and raw multimedia documents. The proposed approach utilizes as input
visual content analysis results, as well as analyzes and exploits associated textual annotation, in order to extract the underlying
semantics, construct a semantic index and classify documents to topics, based on a unified knowledge and semantics representation
model. It may then accept user queries, and, carrying out semantic interpretation and expansion, retrieve documents from the
index and rank them according to user preferences, similarly to text retrieval. All processes are based on a novel semantic
processing methodology, employing fuzzy algebra and principles of taxonomic knowledge representation. The first part of this
work presented in this paper deals with data and knowledge models, manipulation of multimedia content annotations and semantic
indexing, while the second part will continue on the use of the extracted semantic information for personalized retrieval.
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4.
Speech is a fundamental means of human communication. Design and construction are social activities. We argue that designers
and builders generate and develop concepts through dialogue. These communicative events are typically not captured. Consequently,
knowledge transfer and reuse opportunities are missed. Our objective is to capture and mine rich, contextual, social communicative
events for further knowledge reuse. We present a methodology and prototype called I-Dialogue that: (1) captures the knowledge
generated during informal communicative events through dialogue, sketching and gestures in the form of unstructured digital
design knowledge corpus; (2) adds structure to the unstructured digital knowledge corpus; and (3) processes the corpus using
an innovative notion disambiguation algorithm in support of knowledge retrieval. The paper concludes with results of evaluation
experiments with I-Dialogue using a testbed of design–construction projects.
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5.
Quantitative usability requirements are a critical but challenging, and hence an often neglected aspect of a usability engineering process. A case study is described where quantitative usability requirements played a key role in the development of a new user interface of a mobile phone. Within the practical constraints of the project, existing methods for determining usability requirements and evaluating the extent to which these are met, could not be applied as such, therefore tailored methods had to be developed. These methods and their applications are discussed. 相似文献
6.
This paper presents a high-performance broad-coverage supervised word sense disambiguation (WSD) system for English verbs
that uses linguistically motivated features and a smoothed maximum entropy machine learning model. We describe three specific
enhancements to our system’s treatment of linguistically motivated features which resulted in the best published results on
SENSEVAL-2 verbs. We then present the results of training our system on OntoNotes data, both the SemEval-2007 task and additional
data. OntoNotes data is designed to provide clear sense distinctions, based on using explicit syntactic and semantic criteria
to group WordNet senses, with sufficient examples to constitute high quality, broad coverage training data. Using similar
syntactic and semantic features for WSD, we achieve performance comparable to that of human taggers, and competitive with
the top results for the SemEval-2007 task. Empirical analysis of our results suggests that clarifying sense boundaries and/or
increasing the number of training instances for certain verbs could further improve system performance.
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7.
In this paper web–based system user interface hybrid recommendation method based on the ant colony metaphor is presented.
We apply the ontology–based user and user interface modeling. The user model is represented as a tuple and user interface
model is represented by a set of connected nodes, what enables suitable user interface design, an interface personalization
and recommendation. The recommendation is performed using ant colony metaphor for selection the most optimal path in the user
interface graph that specifies the user interface parameters for the specified user.
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8.
We introduce a system for sensing complex social systems with data collected from 100 mobile phones over the course of 9 months.
We demonstrate the ability to use standard Bluetooth-enabled mobile telephones to measure information access and use in different
contexts, recognize social patterns in daily user activity, infer relationships, identify socially significant locations,
and model organizational rhythms.
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9.
A number of mobile applications have emerged that allow users to locate one another. However, people have expressed concerns
about the privacy implications associated with this class of software, suggesting that broad adoption may only happen to the
extent that these concerns are adequately addressed. In this article, we report on our work on P eopleF inder, an application that enables cell phone and laptop users to selectively share their locations with others (e.g. friends,
family, and colleagues). The objective of our work has been to better understand people’s attitudes and behaviors towards
privacy as they interact with such an application, and to explore technologies that empower users to more effectively and
efficiently specify their privacy preferences (or “policies”). These technologies include user interfaces for specifying rules
and auditing disclosures, as well as machine learning techniques to refine user policies based on their feedback. We present
evaluations of these technologies in the context of one laboratory study and three field studies.
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10.
Support vector machines (SVMs) have been promising methods for classification and regression analysis due to their solid mathematical
foundations, which include two desirable properties: margin maximization and nonlinear classification using kernels. However,
despite these prominent properties, SVMs are usually not chosen for large-scale data mining problems because their training
complexity is highly dependent on the data set size. Unlike traditional pattern recognition and machine learning, real-world
data mining applications often involve huge numbers of data records. Thus it is too expensive to perform multiple scans on
the entire data set, and it is also infeasible to put the data set in memory. This paper presents a method, Clustering-Based SVM (CB-SVM), that maximizes the SVM performance for very large data sets given a limited amount of resource, e.g., memory. CB-SVM applies
a hierarchical micro-clustering algorithm that scans the entire data set only once to provide an SVM with high quality samples.
These samples carry statistical summaries of the data and maximize the benefit of learning. Our analyses show that the training
complexity of CB-SVM is quadratically dependent on the number of support vectors, which is usually much less than that of
the entire data set. Our experiments on synthetic and real-world data sets show that CB-SVM is highly scalable for very large
data sets and very accurate in terms of classification.
A preliminary version of the paper, “ Classifying Large Data Sets Using SVM with Hierarchical Clusters”, by H. Yu, J. Yang, and J. Han, appeared in Proc. 2003 Int. Conf. on Knowledge Discovery in Databases (KDD'03), Washington, DC, August 2003. However, this submission has substantially extended the previous paper and contains new and
major-value added technical contribution in comparison with the conference publication.
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11.
We present an enhancement towards adaptive video training for PhoneGuide, a digital museum guidance system for ordinary camera-equipped
mobile phones. It enables museum visitors to identify exhibits by capturing photos of them. In this article, a combined solution
of object recognition and pervasive tracking is extended to a client–server-system for improving data acquisition and for
supporting scale-invariant object recognition. A static as well as a dynamic training technique are presented that preprocess
the collected object data differently and apply two types of neural networks (NN) for classification. Furthermore, the system
enables a temporal adaptation for ensuring a continuous data acquisition to improve the recognition rate over time. A formal
field experiment reveals current recognition rates and indicates the practicability of both methods under realistic conditions
in a museum.
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12.
The complexity of group dynamics occurring in small group interactions often hinders the performance of teams. The availability
of rich multimodal information about what is going on during the meeting makes it possible to explore the possibility of providing
support to dysfunctional teams from facilitation to training sessions addressing both the individuals and the group as a whole.
A necessary step in this direction is that of capturing and understanding group dynamics. In this paper, we discuss a particular
scenario, in which meeting participants receive multimedia feedback on their relational behaviour, as a first step towards
increasing self-awareness. We describe the background and the motivation for a coding scheme for annotating meeting recordings
partially inspired by the Bales’ Interaction Process Analysis. This coding scheme was aimed at identifying suitable observable
behavioural sequences. The study is complemented with an experimental investigation on the acceptability of such a service.
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13.
Tracking location is challenging due to the numerous constraints of practical systems including, but not limited to global
cost, device volume and weight, scalability and accuracy; these constraints are typically more severe for systems that should
be wearable and used indoors. We investigate the use of wearable solar cells to track changing light conditions (a concept
that we named LuxTrace) as a source of user displacement and activity data. We evaluate constraints of this approach and present
results from an experimental validation of displacement and activity estimation. The results indicate that a distance estimation
accuracy of 21 cm (80% quantile) can be achieved. A simple method to combine LuxTrace with complementary absolute location
estimation methods is also presented. We apply carpet-like distributed RFID tags to demonstrate online learning of new lighting
environments.
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14.
This paper describes the simulated car racing competition that was arranged as part of the 2007 IEEE Congress on Evolutionary
Computation. Both the game that was used as the domain for the competition, the controllers submitted as entries to the competition
and its results are presented. With this paper, we hope to provide some insight into the efficacy of various computational
intelligence methods on a well-defined game task, as well as an example of one way of running a competition. In the process,
we provide a set of reference results for those who wish to use the simplerace game to benchmark their own algorithms. The paper is co-authored by the organizers and participants of the competition.
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15.
The European Union co-funded COMUNICAR (communication multimedia unit inside car) project designed and developed an integrated multimedia human–machine interface (HMI) able to manage a wide variety of driver information systems (from entertainment to safety). COMUNICAR proposed an innovative information provision paradigm, in which the on-vehicle HMI is able to tailor the delivery of the information in real time according to the actual driving context and the drivers workload. COMUNICAR adopted a user-centred design process involving an iterative development based on extensive user tests since the early phases of the project. This approach was particularly useful to define and improve the layout of the user interface and specify the rules that decide the scheduling and the modalities of the delivery of the information messages to the driver. This paper introduces the COMUNICAR concept and the user-centred flow of design. Then, a concrete case of user-test driven, iterative improvement of a systems functionality is presented. We also briefly describe two software tools that we have designed to enhance the development process in a user-centred perspective. Finally, the future evolution of the concept of smart and safe information scheduling is sketched and discussed. 相似文献
16.
The article explores approaches to discourses concerning age, with different agendas and national contexts. The Dialogue Seminar
Method is introduced, as a means of facilitating reflection and access to tacit knowledge. Democratic dialogue requires orchestration,
and enables horizontal communication and collective reflection.
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17.
Speech interfaces are becoming more and more popular as a means to interact with virtual environments but the development
and integration of these interfaces is usually still ad hoc, especially the speech grammar creation of the speech interface
is a process commonly performed by hand. In this paper, we introduce an approach to automatically generate a speech grammar
which is generated using semantic information. The semantic information is represented through ontologies and gathered from
the conceptual modelling phase of the virtual environment application. The utterances of the user will be resolved using queries
onto these ontologies such that the meaning of the utterance can be resolved. For validation purposes we augmented a city
park designer with our approach. Informal tests validate our approach, because they reveal that users mainly use words represented
in the semantic data, and therefore also words which are incorporated in the automatically generated speech grammar.
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18.
Traditional content-based music retrieval systems retrieve a specific music object which is similar to what a user has requested.
However, the need exists for the development of category search for the retrieval of a specific category of music objects
which share a common semantic concept. The concept of category search in content-based music retrieval is subjective and dynamic.
Therefore, this paper investigates a relevance feedback mechanism for category search of polyphonic symbolic music based on
semantic concept learning. For the consideration of both global and local properties of music objects, a segment-based music
object modeling approach is presented. Furthermore, in order to discover the user semantic concept in terms of discriminative
features of discriminative segments, a concept learning mechanism based on data mining techniques is proposed to find the
discriminative characteristics between relevant and irrelevant objects. Moreover, three strategies, the Most-Positive, the
Most-Informative, and the Hybrid, to return music objects concerning user relevance judgments are investigated. Finally, comparative
experiments are conducted to evaluate the effectiveness of the proposed relevance feedback mechanism. Experimental results
show that, for a database of 215 polyphonic music objects, 60% average precision can be achieved through the use of the proposed
relevance feedback mechanism.
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19.
We present a study of using camera-phones and visual-tags to access mobile services. Firstly, a user-experience study is described in which participants were both observed learning to interact with a prototype mobile service and interviewed
about their experiences. Secondly, a pointing-device task is presented in which quantitative data was gathered regarding the speed and accuracy with which participants aimed and clicked
on visual-tags using camera-phones. We found that participants’ attitudes to visual-tag-based applications were broadly positive,
although they had several important reservations about camera-phone technology more generally. Data from our pointing-device
task demonstrated that novice users were able to aim and click on visual-tags quickly (well under 3 s per pointing-device
trial on average) and accurately (almost all meeting our defined speed/accuracy tradeoff of 6% error-rate). Based on our findings,
design lessons for camera-phone and visual-tag applications are presented.
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