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1.
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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2.
In a globalised economy the accessibility of services becomes increasingly important for businesses. This has led to a demand
that information systems should be ubiquitous in the sense that they are available to all users under all circumstances, everywhere
and at all times, and independent of the access devices and channels used. The authors believe the key to meeting that demand
is existence of an omnipresent media of interaction and existence of information systems that within that media adapt themselves
to context parameters at run-time. The World Wide Web is considered as that omnipresent media. Thus, the task is left to design
adaptive information systems in a way that avoids unnecessary replication. In this article it will be shown how context parameters
can be utilised to enable system adaptivity. The latter is supposed to increase usability and targets the quality of use,
the content, and the functionality. We propose using an algebraic approach that aids in providing the leanest appropriate
interface via user typing and story boarding. Our approach furthermore limits the content delivered to a user to the amount
that can be dealt with in a usage scenario. The latter is based on defining hyphenation points within the content.
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3.
The new HRS method for hyperlink recommendation based on positive and confined negative association rules is presented in
the paper. Discovered with the new PANAMA algorithm rules are merged and used in the form of recommendation functions, both
to assess the existing hyperlinks and to suggest new ones. Positively and negatively verified and new hyperlinks are presented
to the content manager and can considerably facilitate the maintenance of the web site structure and its adjustment to user
behaviour. The experiments confirmed the usefulness of the Hyperlink Recommender System (HRS) and in particular, of negative
recommendations based on confined negative association rules.
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4.
Provision of personalized recommendations to users requires accurate modeling of their interests and needs. This work proposes
a general framework and specific methodologies for enhancing the accuracy of user modeling in recommender systems by importing
and integrating data collected by other recommender systems. Such a process is defined as user models mediation. The work
discusses the details of such a generic user modeling mediation framework. It provides a generic user modeling data representation
model, demonstrates its compatibility with existing recommendation techniques, and discusses the general steps of the mediation.
Specifically, four major types of mediation are presented: cross-user, cross-item, cross-context, and cross-representation.
Finally, the work reports the application of the mediation framework and illustrates it with practical mediation scenarios.
Evaluations of these scenarios demonstrate the potential benefits of user modeling data mediation, as in certain conditions
it allows improving the quality of the recommendations provided to the users.
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5.
Adaptive information filtering is a challenging and fascinating problem. It requires the adaptation of a representation of
a user’s multiple interests to various changes in them. We tackle this dynamic problem with Nootropia, a model inspired by
the autopoietic view of the immune system. It is based on a self-organising antibody network that reacts to user feedback
in order to define and preserve the user interests. We describe Nootropia in the context of adaptive, content-based document
filtering and evaluate it using virtual users. The results demonstrate Nootropia’s ability to adapt to both short-term variations
and more radical changes in the user’s interests, and to dynamically control its size and connectivity in the process. Advantages
over existing approaches to profile adaptation, such as learning algorithms and evolutionary algorithms are also highlighted.
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6.
An important area of Human Reliability Assessment in interactive systems is the ability to understand the causes of human
error and to model their occurrence. This paper investigates a new approach to analysis of task failures based on patterns
of operator behaviour, in contrast with more traditional event-based approaches. It considers, as a case study, a formal model
of an Air Traffic Control system operator’s task which incorporates a simple model of the high-level cognitive processes involved.
The cognitive model is formalised in the CSP process algebra. Various patterns of behaviour that could lead to task failure
are described using temporal logic. Then a model-checking technique is used to verify whether the set of selected behavioural
patterns is sound and complete with respect to the definition of task failure. The decomposition is shown to be incomplete
and a new behavioural pattern is identified, which appears to have been overlooked in the informal analysis of the problem.
This illustrates how formal analysis of operator models can yield fresh insights into how failures may arise in interactive
systems.
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7.
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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8.
The increasing availability of (digital) cultural heritage artefacts offers great potential for increased access to art content,
but also necessitates tools to help users deal with such abundance of information. User-adaptive art recommender systems aim
to present their users with art content tailored to their interests. These systems try to adapt to the user based on feedback
from the user on which artworks he or she finds interesting. Users need to be able to depend on the system to competently
adapt to their feedback and find the artworks that are most interesting to them. This paper investigates the influence of
transparency on user trust in and acceptance of content-based recommender systems. A between-subject experiment ( N = 60) evaluated interaction with three versions of a content-based art recommender in the cultural heritage domain. This
recommender system provides users with artworks that are of interest to them, based on their ratings of other artworks. Version
1 was not transparent, version 2 explained to the user why a recommendation had been made and version 3 showed a rating of
how certain the system was that a recommendation would be of interest to the user. Results show that explaining to the user
why a recommendation was made increased acceptance of the recommendations. Trust in the system itself was not improved by
transparency. Showing how certain the system was of a recommendation did not influence trust and acceptance. A number of guidelines
for design of recommender systems in the cultural heritage domain have been derived from the study’s results.
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9.
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
10.
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
11.
In spite of significant improvements in video data retrieval, a system has not yet been developed that can adequately respond
to a user’s query. Typically, the user has to refine the query many times and view query results until eventually the expected
videos are retrieved from the database. The complexity of video data and questionable query structuring by the user aggravates
the retrieval process. Most previous research in this area has focused on retrieval based on low-level features. Managing
imprecise queries using semantic (high-level) content is no easier than queries based on low-level features due to the absence
of a proper continuous distance function. We provide a method to help users search for clips and videos of interest in video
databases. The video clips are classified as interesting and uninteresting based on user browsing. The attribute values of clips are classified by commonality, presence, and frequency within each
of the two groups to be used in computing the relevance of each clip to the user’s query. In this paper, we provide an intelligent
query structuring system, called I-Quest, to rank clips based on user browsing feedback, where a template generation from the set of interesting and uninteresting
sets is impossible or yields poor results.
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12.
As the Internet has been commonly used in our everyday lives, we have been able to obtain large amount of information from
it, whereas we have simultaneously had a problem that it is difficult to find proper information for us from the large amount
of information on the Web. Although many information recommendation methods have been proposed in order to solve this problem,
most recommendation methods are based on a large amount of user’s personal data such as operation log, schedule, etc – which
means that we have to manage a large amount of personal data in the system in order to provide proper information to users,
and it would be expensive to construct such a system.
With this background, in this study, against aiming to construct a sophisticated information recommendation system based on
large personal data, we propose a handy and not expensive information recommendation method, working beside a normal search
engine, which does not depend on user profile data, but on topical news information.
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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.
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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15.
Nowadays data mining plays an important role in decision making. Since many organizations do not possess the in-house expertise
of data mining, it is beneficial to outsource data mining tasks to external service providers. However, most organizations
hesitate to do so due to the concern of loss of business intelligence and customer privacy. In this paper, we present a Bloom
filter based solution to enable organizations to outsource their tasks of mining association rules, at the same time, protect
their business intelligence and customer privacy. Our approach can achieve high precision in data mining by trading-off the
storage requirement.
This research was supported by the USA National Science Foundation Grants CCR-0310974 and IIS-0546027.
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16.
We provide the complete record of methodology that let us evolve BrilliAnt, the winner of the Ant Wars contest. Ant Wars contestants are virtual ants collecting food on a grid board in the presence
of a competing ant. BrilliAnt has been evolved through a competitive one-population coevolution using genetic programming
and fitnessless selection. In this paper, we detail the evolutionary setup that lead to BrilliAnt’s emergence, assess its
direct and indirect human-competitiveness, and describe the behavioral patterns observed in its strategy.
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17.
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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18.
In this paper, we present a new kind of mobile ad hoc application, which we call mobile profile based distributed grouping (MoPiDiG), which is a combination of mobile clustering and data clustering. In MoPiDiG, each mobile host is endowed with a user profile and, while the users move around, hosts with similar profiles are found and a robust mobile group is formed. The members of a group are able to cooperate with each other or attain a goal together. In this article, MoPiDiG is defined and compared with related approaches. Furthermore, a modular architecture and algorithms are presented to build arbitrary MoPiDiG applications. 相似文献
19.
In this study, we intend to examine information retrieval behaviors from a psychological point of view using a search engine
on the World Wide Web (WWW). We investigated information retrieving behaviors in detail based on both the recorded data of
retrievers’ web browsing actions and their thinking processes by the “think aloud” method. We focused on selected keywords
for retrieving and compared them between retrievers who had enough knowledge about their task and those who did not. Our goal
was to learn about the literacy needed for finding required information efficiently on the WWW.
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20.
In the near future, our life will normally be surrounded with fairly complicated artifacts, enabled by the autonomous robot
and brain–machine interface technologies. In this paper, we argue that what we call the responsibility flaw problem and the
inappropriate use problem need to be overcome in order for us to benefit from complicated artifacts. In order to solve these
problems, we propose an approach to endowing artifacts with an ability of socially communicating with other agents based on
the artifact-as-a-half-mirror metaphor. The idea is to have future artifacts behave according to the hybrid intention composed
of the owner’s intention and the social rules. We outline the approach and discuss its feasibility together with preliminary
work.
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