Abstract: The advent of the Internet, mobile devices and social media is revolutionizing the experience of retail customers by linking multiple sources through various channels. Omnichannel retailing is a retailing that combines multiple channels to allow customers to seamlessly leverage all the distribution information online and offline while shopping. Therefore, today data are an asset more critical than ever for all organizations. Nonetheless, because of its heterogeneity through platforms, developers are currently facing difficulties in dealing with personal data. Considering the possibilities of omnichannel communication, this paper presents channel categorization that could enhance the customer experience of omnichannel center called hyper center. The purpose of this paper is fundamentally to describe the connection between the omnichannel hyper center and the customer, with particular attention to privacy protection. The first phase was finding the most appropriate channels of communication for hyper center. Consequently, a selection of widely used communication channels has been identified and analyzed with regard to the effect requirements for optimizing user experience. The evaluation criteria are divided into 3 groups: general, user profile and channel options. For each criterion the weight of importance for omnichannel communication was defined. The most important thing was to consider how the hyper center can make user identification while respecting the privacy protection requirements. The study carried out also shows what customer experience across digital networks would look like, based on an omnichannel approach owing to privacy protection principles.
Abstract: The telemedicine services require correct computing resource management to guarantee productivity and efficiency for medical and non-medical staff. The aim of this study was to examine web management strategies to ensure the availability of resources and services in telemedicine so as to provide medical information management with an accessible strategy. In addition, to evaluate the quality-of-service parameters, the followings were measured: delays, throughput, jitter, latency, available bandwidth, percent of access and denial of services based of web management performance map with profiles permissions and database management. Through 24 different test scenarios, the results show 100% in availability of medical information, in relation to access of medical staff to web services, and quality of service (QoS) of 99% because of network delay and performance of computer network. The findings of this study suggest that the proposed strategy of web management is an ideal solution to guarantee the availability, reliability, and accessibility of medical information. Finally, this strategy offers seven user profile used at telemedicine center of Bogota-Colombia keeping QoS parameters suitable to telemedicine services.
Abstract: One of the significant issues facing web users is the amount of noise in web data which hinders the process of finding useful information in relation to their dynamic interests. Current research works consider noise as any data that does not form part of the main web page and propose noise web data reduction tools which mainly focus on eliminating noise in relation to the content and layout of web data. This paper argues that not all data that form part of the main web page is of a user interest and not all noise data is actually noise to a given user. Therefore, learning of noise web data allocated to the user requests ensures not only reduction of noisiness level in a web user profile, but also a decrease in the loss of useful information hence improves the quality of a web user profile. Noise Web Data Learning (NWDL) tool/algorithm capable of learning noise web data in web user profile is proposed. The proposed work considers elimination of noise data in relation to dynamic user interest. In order to validate the performance of the proposed work, an experimental design setup is presented. The results obtained are compared with the current algorithms applied in noise web data reduction process. The experimental results show that the proposed work considers the dynamic change of user interest prior to elimination of noise data. The proposed work contributes towards improving the quality of a web user profile by reducing the amount of useful information eliminated as noise.
Abstract: Nowadays websites provide a vast number of resources for users. Recommender systems have been developed as an essential element of these websites to provide a personalized environment for users. They help users to retrieve interested resources from large sets of available resources. Due to the dynamic feature of user preference, constructing an appropriate model to estimate the user preference is the major task of recommender systems. Profile matching and latent factors are two main approaches to identify user preference. In this paper, we employed the latent factor and profile matching to cluster the user profile and identify user preference, respectively. The method uses the Distance Dependent Chines Restaurant Process as a Bayesian nonparametric framework to extract the latent factors from the user profile. These latent factors are mapped to user interests and a weighted distribution is used to identify user preferences. We evaluate the proposed method using a real-world data-set that contains news tweets of a news agency (BBC). The experimental results and comparisons show the superior recommendation accuracy of the proposed approach related to existing methods, and its ability to effectively evolve over time.
Abstract: In the past decade, the social networking app has been growing very rapidly. Geolocation data is one of the important features of social media that can attach the user's location coordinate in the real world. This paper proposes the use of geolocation data from the Twitter social media application to gain knowledge about urban dynamics, especially on human mobility behavior. This paper aims to explore the relation between geolocation Twitter with the existence of people in the urban area. Firstly, the study will analyze the spread of people in the particular area, within the city using Twitter social media data. Secondly, we then match and categorize the existing place based on the same individuals visiting. Then, we combine the Twitter data from the tracking result and the questionnaire data to catch the Twitter user profile. To do that, we used the distribution frequency analysis to learn the visitors’ percentage. To validate the hypothesis, we compare it with the local population statistic data and land use mapping released by the city planning department of Makassar local government. The results show that there is the correlation between Twitter geolocation and questionnaire data. Thus, integration the Twitter data and survey data can reveal the profile of the social media users.
Abstract: The rapid growth of the human population and the
environmental degradation associated with increased consumption of
resources raises concerns on sustainability. Social sustainability
constitutes one of the three dimensions of sustainability together with
environmental and economic dimensions. Even though there is not an
agreement on what social sustainability consists of, it is a well known
fact that it necessitates user participation. The fore, this study aims to
observe and analyze the role of user participation on social
sustainability. In this paper, the links between user participation and indicators of
social sustainability have been searched. In order to achieve this, first
of all a literature review on social sustainability has been done;
accordingly, the information obtained from researches has been used
in the evaluation of the projects conducted in the developing
countries considering user participation. These examples are taken as
role models with pros and cons for the development of the checklist
for the evaluation of the case studies. Furthermore, a case study over
the post earthquake residential settlements in Turkey have been
conducted. The case study projects are selected considering different building
scales (differing number of residential units), scale of the problem
(post-earthquake settlements, rehabilitation of shanty dwellings) and
the variety of users (differing socio-economic dimensions). Decisionmaking,
design, building and usage processes of the selected projects
and actors of these processes have been investigated in the context of
social sustainability. The cases include: New Gourna Village by
Hassan Fathy, Quinta Monroy dwelling units conducted in Chile by
Alejandro Aravena and Beyköy and Beriköy projects in Turkey
aiming to solve the problem of housing which have appeared after the
earthquake happened in 1999 have been investigated. Results of the
study possible links between social sustainability indicators and user
participation and links between user participation and the
peculiarities of place. Results are compared and discussed in order to find possible
solutions to form social sustainability through user participation.
Results show that social sustainability issues depend on communities'
characteristics, socio-economic conditions and user profile but user
participation has positive effects on some social sustainability
indicators like user satisfaction, a sense of belonging and social
stability.
Abstract: E-Learning enables the users to learn at anywhere at
any time. In E-Learning systems, authenticating the E-Learning user
has security issues. The usage of appropriate communication
networks for providing the internet connectivity for E-learning is
another challenge. WiMAX networks provide Broadband Wireless
Access through the Multicast Broadcast Service so these networks
can be most suitable for E-Learning applications. The authentication
of E-Learning user is vulnerable to session hijacking problems. The
repeated authentication of users can be done to overcome these
issues. In this paper, session based Profile Caching Authentication is
proposed. In this scheme, the credentials of E-Learning users can be
cached at authentication server during the initial authentication
through the appropriate subscriber station. The proposed cache based
authentication scheme performs fast authentication by using cached
user profile. Thus, the proposed authentication protocol reduces the
delay in repeated authentication to enhance the security in ELearning.
Abstract: Recently, Job Recommender Systems have gained
much attention in industries since they solve the problem of
information overload on the recruiting website. Therefore, we
proposed Extended Personalized Job System that has the capability of
providing the appropriate jobs for job seeker and recommending
some suitable information for them using Data Mining Techniques
and Dynamic User Profile. On the other hands, company can also
interact to the system for publishing and updating job information.
This system have emerged and supported various platforms such as
web application and android mobile application. In this paper, User
profiles, Implicit User Action, User Feedback, and Clustering
Techniques in WEKA libraries were applied and implemented. In
additions, open source tools like Yii Web Application Framework,
Bootstrap Front End Framework and Android Mobile Technology
were also applied.
Abstract: Communicating users' needs, goals and problems help
designers and developers overcome challenges faced by end users.
Personas are used to represent end users’ needs. In our research,
creating personas allowed the following questions to be answered:
Who are the potential user groups? What do they want to achieve by
using the service? What are the problems that users face? What
should the service provide to them? To develop realistic personas, we
conducted a focus group discussion with undergraduate and graduate
students and also interviewed a university librarian. The personas
were created to help evaluating the Institutional Repository that is
based on the DSpace system. The profiles helped to communicate
users' needs, abilities, tasks, and problems, and the task scenarios
used in the heuristic evaluation were based on these personas. Four
personas resulted of a focus group discussion with undergraduate and
graduate students and from interviewing a university librarian. We
then used these personas to create focused task-scenarios for a
heuristic evaluation on the system interface to ensure that it met
users' needs, goals, problems and desires. In this paper, we present
the process that we used to create the personas that led to devise the
task scenarios used in the heuristic evaluation as a follow up study of
the DSpace university repository.
Abstract: We have proposed an information filtering system
using index word selection from a document set based on the
topics included in a set of documents. This method narrows
down the particularly characteristic words in a document set
and the topics are obtained by Sparse Non-negative Matrix
Factorization. In information filtering, a document is often
represented with the vector in which the elements correspond
to the weight of the index words, and the dimension of the
vector becomes larger as the number of documents is
increased. Therefore, it is possible that useless words as index
words for the information filtering are included. In order to
address the problem, the dimension needs to be reduced. Our
proposal reduces the dimension by selecting index words
based on the topics included in a document set. We have
applied the Sparse Non-negative Matrix Factorization to the
document set to obtain these topics. The filtering is carried out
based on a centroid of the learning document set. The centroid
is regarded as the user-s interest. In addition, the centroid is
represented with a document vector whose elements consist of
the weight of the selected index words. Using the English test
collection MEDLINE, thus, we confirm the effectiveness of
our proposal. Hence, our proposed selection can confirm the
improvement of the recommendation accuracy from the other
previous methods when selecting the appropriate number of
index words. In addition, we discussed the selected index
words by our proposal and we found our proposal was able to
select the index words covered some minor topics included in
the document set.
Abstract: The information on the Web increases tremendously.
A number of search engines have been developed for searching Web
information and retrieving relevant documents that satisfy the
inquirers needs. Search engines provide inquirers irrelevant
documents among search results, since the search is text-based rather
than semantic-based. Information retrieval research area has
presented a number of approaches and methodologies such as
profiling, feedback, query modification, human-computer interaction,
etc for improving search results. Moreover, information retrieval has
employed artificial intelligence techniques and strategies such as
machine learning heuristics, tuning mechanisms, user and system
vocabularies, logical theory, etc for capturing user's preferences and
using them for guiding the search based on the semantic analysis
rather than syntactic analysis. Although a valuable improvement has
been recorded on search results, the survey has shown that still
search engines users are not really satisfied with their search results.
Using ontologies for semantic-based searching is likely the key
solution. Adopting profiling approach and using ontology base
characteristics, this work proposes a strategy for finding the exact
meaning of the query terms in order to retrieve relevant information
according to user needs. The evaluation of conducted experiments
has shown the effectiveness of the suggested methodology and
conclusion is presented.
Abstract: This study proposes a new recommender system based on the collaborative folksonomy. The purpose of the proposed system is to recommend Internet resources (such as books, articles, documents, pictures, audio and video) to users. The proposed method includes four steps: creating the user profile based on the tags, grouping the similar users into clusters using an agglomerative hierarchical clustering, finding similar resources based on the user-s past collections by using content-based filtering, and recommending similar items to the target user. This study examines the system-s performance for the dataset collected from “del.icio.us," which is a famous social bookmarking website. Experimental results show that the proposed tag-based collaborative and content-based filtering hybridized recommender system is promising and effectiveness in the folksonomy-based bookmarking website.
Abstract: Social Business Process Management (SBPM)
promises to overcome limitations of traditional BPM by allowing
flexible process design and enactment through the involvement of
users from a social community. This paper proposes a meta-model
and architecture for socially driven business process management
systems. It discusses the main facets of the architecture such as goalbased
role assignment that combines social recommendations with
user profile, and process recommendation, through a real example of
a charity organization.
Abstract: The paper focuses on the area of context modeling with respect to the specification of context-aware systems supporting ubiquitous applications. The proposed approach, followed within the SIMPLICITY IST project, uses a high-level system ontology to derive context models for system components which consequently are mapped to the system's physical entities. For the definition of user and device-related context models in particular, the paper suggests a standard-based process consisting of an analysis phase using the Common Information Model (CIM) methodology followed by an implementation phase that defines 3GPP based components. The benefits of this approach are further depicted by preliminary examples of XML grammars defining profiles and components, component instances, coupled with descriptions of respective ubiquitous applications.
Abstract: The human friendly interaction is the key function of a human-centered system. Over the years, it has received much attention to develop the convenient interaction through intention recognition. Intention recognition processes multimodal inputs including speech, face images, and body gestures. In this paper, we suggest a novel approach of intention recognition using a graph representation called Intention Graph. A concept of valid intention is proposed, as a target of intention recognition. Our approach has two phases: goal recognition phase and intention recognition phase. In the goal recognition phase, we generate an action graph based on the observed actions, and then the candidate goals and their plans are recognized. In the intention recognition phase, the intention is recognized with relevant goals and user profile. We show that the algorithm has polynomial time complexity. The intention graph is applied to a simple briefcase domain to test our model.
Abstract: With the advent of emerging personal computing paradigms such as ubiquitous and mobile computing, Web contents are becoming accessible from a wide range of mobile devices. Since these devices do not have the same rendering capabilities, Web contents need to be adapted for transparent access from a variety of client agents. Such content adaptation results in better rendering and faster delivery to the client device. Nevertheless, Web content adaptation sets new challenges for semantic markup. This paper presents an advanced components platform, called MorfeoSMC, enabling the development of mobility applications and services according to a channel model based on Services Oriented Architecture (SOA) principles. It then goes on to describe the potential for integration with the Semantic Web through a novel framework of external semantic annotation of mobile Web contents. The role of semantic annotation in this framework is to describe the contents of individual documents themselves, assuring the preservation of the semantics during the process of adapting content rendering, as well as to exploit these semantic annotations in a novel user profile-aware content adaptation process. Semantic Web content adaptation is a way of adding value to and facilitates repurposing of Web contents (enhanced browsing, Web Services location and access, etc).
Abstract: In blended learning environments, the Internet can be combined with other technologies. The aim of this research was to design, introduce and validate a model to support synchronous and asynchronous activities by managing content domains in an Adaptive Hypermedia System (AHS). The application is based on information recovery techniques, clustering algorithms and adaptation rules to adjust the user's model to contents and objects of study. This system was applied to blended learning in higher education. The research strategy used was the case study method. Empirical studies were carried out on courses at two universities to validate the model. The results of this research show that the model had a positive effect on the learning process. The students indicated that the synchronous and asynchronous scenario is a good option, as it involves a combination of work with the lecturer and the AHS. In addition, they gave positive ratings to the system and stated that the contents were adapted to each user profile.
Abstract: A model of user behaviour based automated planning
is introduced in this work. The behaviour of users of web interactive
systems can be described in term of a planning domain encapsulating
the timed actions patterns representing the intended user profile. The
user behaviour recognition is then posed as a planning problem
where the goal is to parse a given sequence of user logs of the
observed activities while reaching a final state.
A general technique for transforming a timed finite state automata
description of the behaviour into a numerical parameter planning
model is introduced.
Experimental results show that the performance of a planning
based behaviour model is effective and scalable for real world
applications. A major advantage of the planning based approach is to
represent in a single automated reasoning framework problems of
plan recognitions, plan synthesis and plan optimisation.
Abstract: As communications systems and technology become more advanced and complex, it will be increasingly important to focus on users- individual needs. Personalization and effective user profile management will be necessary to ensure the uptake and success of new services and devices and it is therefore important to focus on the users- requirements in this area and define solutions that meet these requirements. The work on personalization and user profiles emerged from earlier ETSI work on a Universal Communications Identifier (UCI) which is a unique identifier of the user rather than a range of identifiers of the many of communication devices or services (e.g. numbers of fixed phone at home/work, mobile phones, fax and email addresses). This paper describes work on personalization including standardized information and preferences and an architectural framework providing a description of how personalization can be integrated in Next Generation Networks, together with the UCI concept.
Abstract: In the current age, retrieval of relevant information
from massive amount of data is a challenging job. Over the years,
precise and relevant retrieval of information has attained high
significance. There is a growing need in the market to build systems,
which can retrieve multimedia information that precisely meets the
user's current needs. In this paper, we have introduced a framework
for refining query results before showing it to the user, using ambient
intelligence, user profile, group profile, user location, time, day, user
device type and extracted features. A prototypic tool was also
developed to demonstrate the efficiency of the proposed approach.