Sections, categories and keywords as interest specification tools for personalised news services

2001 ◽  
Vol 25 (3) ◽  
pp. 149-160 ◽  
Author(s):  
Alberto Díaz ◽  
Pablo Gervás ◽  
Antonio García ◽  
Inmaculada Chacón
Keyword(s):  
User Satisfaction ◽  
General Information ◽  
Test Cases ◽  
User Interest ◽  
General Applicability ◽  
Digital News ◽  
Actual Evaluation ◽  
Close Study ◽  
News Services ◽  
Evaluation Of System Performance

Through an evaluation of system performance and user satisfaction for the Mercurio system, considers the general applicability and usefulness of different methods of specifying user interest for the general case of digital news services. Outlines the specific characteristics distinguishing such systems from more general information systems and discusses their effect. Proposes an evaluation blueprint for them starting from information retrieval procedures, existing work on search engine evaluation, and a close study of the working principles and the required evaluation according to the particular properties and conditions of the services under consideration. Presents and discusses actual evaluation results for system tests based both on real users and customised test cases. Conclusions cover the nature of the information handling tasks that digital news services are faced with, the relative merits of sections, categories and keywords with respect to this particular set of tasks, and the risks of careless application of recall and precision measures in systems such as these.

News consumption of hard and soft topics in Spain: Sources, formats and access routes

2020 ◽  
Vol 45 (2) ◽  
pp. 198-222
Author(s):  
María Pilar Martínez-Costa ◽  
Cristina Sánchez-Blanco ◽  
Javier Serrano-Puche
Keyword(s):  
Social Networks ◽  
Online Information ◽  
User Interest ◽  
News Report ◽  
News Stories ◽  
News Consumption ◽  
Soft News ◽  
Digital News ◽  
Arts And Culture ◽  
Regional Community

AbstractThe variety of devices and the socialization of consumption have decentralized access to online information which is not retrieved directly from media websites but through social networks. These same factors have driven user interest towards a wider range of both ‘hard’ and ‘soft’ topics. The aim of this article is to identify the consumption of news on these topics among digital users in Spain. The methodology used is based on an analysis of the survey conducted as part of the Digital News Report 2017. Following this analysis, a conclusion has been reached that the most popular hard news stories in Spain are those related to the local and regional community itself, and to health and education, while the most popular soft news stories relate to lifestyles and arts and culture. The analysis has revealed that increased interest in news and greater topic specialization result in more diversified use of sources, formats, and complementary routes.

scholarly journals Evaluation of Hypermedia Tools in Terms of Usability Heuristics for English Language Teaching

2021 ◽  
pp. 133-149
Author(s):  
Vikas Rao Naidu ◽  
Shyamala Srinivas ◽  
Mahmood Al Raisi ◽  
Vishal Dattana
Keyword(s):  
Language Learning ◽  
User Satisfaction ◽  
Teaching And Learning ◽  
English Language ◽  
Learning Experience ◽  
Design Guidelines ◽  
English Language Teaching ◽  
Qualitative Assessment ◽  
Smart Devices ◽  
User Interest

The technology-assisted teaching and learning process has seen a spurt in growth in the last two decades. The education technology field has rapidly embraced new tools and techniques to enhance the student learning experience. With the evolution of multimedia elements such as digital images, audio, video, graphics, and animation, the learning supported by technology has made learning flexible and accessible in terms of time and place. With Wi-Fi enabled campuses, it is much easier for students to learn using their smart devices enabled by hypermedia content. Hypermedia, also known as active media, is the multimedia content that brings in interactivity, where the user can interact with the system, rather than viewing the content in passive mode. This helps in generating a dialogue between the system and user, sustaining user interest. Some examples of hypermedia are interactive quizzes, games, interactive videos, etc. This study aims to investigate and evaluate four interactive tools, namely FluentU, Duolingo, Livemocha, and Hello English, which are designed for language learning. A qualitative assessment of the applications, including a review of past literature on language learning using tools, was undertaken. The expert evaluation or assessment was done using Jakob Nielsen’s ten heuristics or design guidelines. The objective was to compare the applications by measuring their usability against the standard heuristics. The goal of any usability study is user satisfaction. Through this interface evaluation, the researchers have concluded for designers that could be considered during future development of hypermedia-based tools.

scholarly journals A Multitask Learning Model with Multiperspective Attention and Its Application in Recommendation

2021 ◽  
Vol 2021 ◽  
pp. 1-13
Author(s):  
Yingshuai Wang ◽  
Dezheng Zhang ◽  
Aziguli Wulamu
Keyword(s):  
User Satisfaction ◽  
Multitask Learning ◽  
Attention And Memory ◽  
User Interest ◽  
Training Models ◽  
User Interests ◽  
Interaction Mode ◽  
Public Data ◽  
Fusion Mode ◽  
Different Characteristics

Training models to predict click and order targets at the same time. For better user satisfaction and business effectiveness, multitask learning is one of the most important methods in e-commerce. Some existing researches model user representation based on historical behaviour sequence to capture user interests. It is often the case that user interests may change from their past routines. However, multi-perspective attention has broad horizon, which covers different characteristics of human reasoning, emotions, perception, attention, and memory. In this paper, we attempt to introduce the multi-perspective attention and sequence behaviour into multitask learning. Our proposed method offers better understanding of user interest and decision. To achieve more flexible parameter sharing and maintaining the special feature advantage of each task, we improve the attention mechanism at the view of expert interactive. To the best of our knowledge, we firstly propose the implicit interaction mode, the explicit hard interaction mode, the explicit soft interaction mode, and the data fusion mode in multitask learning. We do experiments on public data and lab medical data. The results show that our model consistently achieves remarkable improvements to the state-of-the-art method.

scholarly journals Dynamic Modeling and Analysis of Multidimensional Hybrid Recommendation Algorithm in Tourism Itinerary Planning under the Background of Big Data

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yange Hao ◽  
Na Song
Keyword(s):  
Travel Time ◽  
User Satisfaction ◽  
Planning System ◽  
Personalized Recommendation ◽  
User Interest ◽  
Accuracy Rate ◽  
Recommendation Algorithm ◽  
Itinerary Planning ◽  
Travel Planning ◽  
Travel Recommendation

Smart tourism can provide high-quality and convenient services for different tourists, and tourism itinerary planning system can simplify tourists’ tourism preparation. In order to improve the limitation of the recommendation dimension of traditional travel planning system, this paper designs a mixed user interest model on the premise of traditional user interest modeling and combines various attributes of scenic spots to form personalized recommendation of scenic spots. Then, it uses heuristic travel planning cost-effective method to construct the corresponding travel planning system for travel planning. In terms of the accuracy rate of travel planning recommendation, the accuracy rate of multidimensional hybrid travel recommendation algorithm is 0.984, and the missing rate is 0. When the travel cost and travel time are the same and the number of scenic spots is 20–30, the memory occupation of MH algorithm is only 1/2 of that of TM algorithm. The results show that the multidimensional hybrid travel recommendation algorithm can improve the personalized travel planning of users and the travel time efficiency ratio. The results of this study have a certain reference value in improving user satisfaction with the travel planning system and reducing user interaction.

REQUIREMENT BASED SYSTEM TEST CASE PRIORITIZATION OF NEW AND REGRESSION TEST CASES

2009 ◽  
Vol 19 (03) ◽  
pp. 453-475 ◽  
Author(s):  
R. KRISHNAMOORTHI ◽  
S. A. SAHAAYA ARUL MARY
Keyword(s):  
Fault Detection ◽  
User Satisfaction ◽  
Cost Effective ◽  
System Level ◽  
Performance Goals ◽  
Test Case ◽  
Test Cases ◽  
Test Case Prioritization ◽  
Code Coverage ◽  
Effective Manner

Test case prioritization schedules the test cases in an order that increases the effectiveness in achieving some performance goals. One of the most important performance goals is the rate of fault detection. Test cases should run in an order that increases the possibility of fault detection and also detects the most severe faults at the earliest in its testing life cycle. Test case prioritization techniques have proved to be beneficial for improving regression testing activities. While code coverage based prioritization techniques are found to be studied by most scholars, test case prioritization based on requirements in a cost effective manner has not been used for studies so far. Hence, in this paper, we propose to put forth a model for system level Test Case Prioritization (TCP) from software requirement specification to improve user satisfaction with quality software that can also be cost effective and to improve the rate of severe fault detection. The proposed model prioritizes the system test cases based on six factors: customer priority, changes in requirement, implementation complexity, usability, application flow and fault impact. The proposed prioritization technique is experimented in three phases with student projects and two sets of industrial projects and the results show convincingly that the proposed prioritization technique improves the rate of severe fault detection.

scholarly journals Unified Representation of Twitter and Online News Using Graph and Entities

2021 ◽  
Vol 4 ◽  
Author(s):  
Munira Syed ◽  
Daheng Wang ◽  
Meng Jiang ◽  
Oliver Conway ◽  
Vishal Juneja ◽  
...  
Keyword(s):  
Social Media ◽  
Online News ◽  
Consumer Engagement ◽  
Digital Platforms ◽  
Digital News ◽  
News Agencies ◽  
Timely Fashion ◽  
Unification Problem ◽  
Different Content ◽  
News Services

To improve consumer engagement and satisfaction, online news services employ strategies for personalizing and recommending articles to their users based on their interests. In addition to news agencies’ own digital platforms, they also leverage social media to reach out to a broad user base. These engagement efforts are often disconnected with each other, but present a compelling opportunity to incorporate engagement data from social media to inform their digital news platform and vice-versa, leading to a more personalized experience for users. While this idea seems intuitive, there are several challenges due to the disparate nature of the two sources. In this paper, we propose a model to build a generalized graph of news articles and tweets that can be used for different downstream tasks such as identifying sentiment, trending topics, and misinformation, as well as sharing relevant articles on social media in a timely fashion. We evaluate our framework on a downstream task of identifying related pairs of news articles and tweets with promising results. The content unification problem addressed by our model is not unique to the domain of news, and thus can be applicable to other problems linking different content platforms.

A PERSONALIZED IMAGE RETRIEVAL BASED ON USER INTEREST MODEL

2010 ◽  
Vol 24 (03) ◽  
pp. 401-419 ◽  
Author(s):  
JING ZHANG ◽  
LI ZHUO ◽  
LANSUN SHEN ◽  
LIN HE
Keyword(s):  
Image Retrieval ◽  
User Satisfaction ◽  
Clustering Algorithm ◽  
Visual Features ◽  
Semantic Features ◽  
User Interest ◽  
Short Term ◽  
Interest Model ◽  
User Interest Model

In order to narrow the semantic gap, user interest model plays an important role in personalized image retrieval. A novel personalized image retrieval approach based on user interest model is proposed in this study. User interest model is developed on the basis of short-tem and long-term interests. (1) Short-term interests are represented by collecting visual and semantic features. Visual features are collected by MARS relevance feedback. Semantic features are constructed by building a mapping from image low-level visual features to high-level semantic features on the basis of SVM. (2) Long-term interests are inferred by inference engine from the collected short-term interests. Long-term visual features are collected by the nonlinear gradual forgetting interest inference algorithm and semantic features are obtained by clustering algorithm. After applying to image retrieval, experimental results show that the average recall/precision is significantly improved and a better user satisfaction rate is achieved as well. Furthermore, it demonstrates our model can be efficiently adapted to user interests and matches personalized image retrieval.

scholarly journals Evaluation of Hypermedia Tools in Terms of Usability Heuristics for English Language Teaching

2021 ◽  
Author(s):  
Vikas Rao Naidu ◽  
Shyamala Srinivas ◽  
Mahmood Al Raisi ◽  
Vishal Dattana
Keyword(s):  
Language Learning ◽  
User Satisfaction ◽  
Teaching And Learning ◽  
English Language ◽  
Learning Experience ◽  
Design Guidelines ◽  
English Language Teaching ◽  
Qualitative Assessment ◽  
Smart Devices ◽  
User Interest

The technology-assisted teaching and learning process has seen a spurt in growth in the last two decades. The education technology field has rapidly embraced new tools and techniques to enhance the student learning experience. With the evolution of multimedia elements such as digital images, audio, video, graphics, and animation, the learning supported by technology has made learning flexible and accessible in terms of time and place. With Wi-Fi enabled campuses, it is much easier for students to learn using their smart devices enabled by hypermedia content. Hypermedia, also known as active media, is the multimedia content that brings in interactivity, where the user can interact with the system, rather than viewing the content in passive mode. This helps in generating a dialogue between the system and user, sustaining user interest. Some examples of hypermedia are interactive quizzes, games, interactive videos, etc. This study aims to investigate and evaluate four interactive tools, namely FluentU, Duolingo, Livemocha, and Hello English, which are designed for language learning. A qualitative assessment of the applications, including a review of past literature on language learning using tools, was undertaken. The expert evaluation or assessment was done using Jakob Nielsen’s ten heuristics or design guidelines. The objective was to compare the applications by measuring their usability against the standard heuristics. The goal of any usability study is user satisfaction. Through this interface evaluation, the researchers have concluded for designers that could be considered during future development of hypermedia-based tools.

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