Search results

Term suggestion is a very useful information retrieval technique that tries to suggest relevant terms for users' queries, to help advertisers find more appropriate terms relevant to their target market. This paper aims to focus on the problem of using several semantic analysis methods to implement a term suggestion system.

Three semantic analysis techniques are adopted – latent semantic indexing (LSI), probabilistic latent semantic indexing (PLSI), and a keyword relationship graph (KRG) – to implement a term suggestion system.

This paper shows that using multiple semantic analysis techniques can give significant performance improvements.

The suggested terms returned from the system may be out of date, since the system uses a batch processing mode to update the training parameter.

The paper shows that the benefit of the techniques is to overcome the problems of synonymy and polysemy over the information retrieval field, by using a vector space model. Moreover, an intelligent stopping strategy is proposed to save the required number of iterations for probabilistic latent semantic indexing.

This study aims to present a new web page recommendation system that can help users to reduce navigational time on the internet.

The proposed design is based on the primacy effect of browsing behavior, that users prefer top ranking items in search results. This approach is intuitive and requires no training data at all.

A user study showed that users are more satisfied with the proposed search methods than with general search engines using hot keywords. Moreover, two performance measures confirmed that the proposed search methods out‐perform other metasearch and search engines.

The research has limitations and future work is planned along several directions. First, the search methods implemented are primarily based on the keyword match between the contents of web pages and the user query items. Using the semantic web to recommend concepts and items relevant to the user query might be very helpful in finding the exact contents that users want, particularly when the users do not have enough knowledge about the domains in which they are searching. Second, offering a mechanism that groups search results to improve the way search results are segmented and displayed also assists users to locate the contents they need. Finally, more user feedback is needed to fine‐tune the search parameters including α and β to improve the performance.

The proposed model can be used to improve the search performance of any search engine.

First, compared with the democratic voting procedure used by metasearch engines, search engine vector voting (SVV) enables a specific combination of search parameters, denoted as α and β, to be applied to a voted search engine, so that users can either narrow or expand their search results to meet their search preferences. Second, unlike page quality analysis, the hyperlink prediction (HLP) determines qualified pages by simply measuring their user behavior function (UBF) values, and thus takes less computing power. Finally, the advantages of HLP over statistical analysis are that it does not need training data, and it can target both multi‐site and site‐specific analysis.

Web‐snippet clustering has recently attracted a lot of attention as a means to provide users with a succinct overview of relevant results compared with traditional search results. This paper seeks to research the building of a web‐snippet clustering system, based on a mixed clustering method.

This paper proposes a mixed clustering method to organise all returned snippets into a hierarchical tree. The method accomplishes two main tasks: one is to construct the cluster labels and the other is to build a hierarchical tree.

Five measures were used to measure the quality of clustering results. Based on the results of the experiments, it was concluded that the performance of the system is better than current commercial and academic systems.

A high performance system is presented, based on the clustering method. A divisive hierarchical clustering algorithm is also developed to organise all returned snippets into a hierarchical tree.

The purpose of this study is to develop resin composite materials composed of polycaprolactone (PCL) acrylates and hydroxyapatite (HA) nanoparticles for ultraviolet digital light projection (DLP) three-dimensional (3D) printing technique.

Two PCL-based triacrylates, namely, glycerol-3 caprolactone-triacrylate (Gly-3CL-TA) and glycerol-6 caprolactone-triacrylate (Gly-6CL-TA) were synthesized from ring-opening polymerization of ε-caprolacton monomer in the presence of glycerol and then acrylation was performed using acryloyl chloride. 3D printing resins made of Gly-3CL-TA or Gly-6CL-TA, 5% HA and 3% of photoinitiator 2,4,6-Trimethylbenzoyl-diphenyl-phosphineoxide were then formulated. The surface topography, surface element composition, flexural strength, flexural modulus, cytotoxicity and degradation of the PCL-based scaffolds were then characterized.

Resin composite composed of Gly-3CL-TA or Gly-6CL-TA and 5% (w/w) of HA can be printed by 405 nm DLP 3D printers. The former has lower viscosity and thus can form a more uniform layer-by-layer structure, while the latter exhibited a higher flexural strength and modulus after being printed. Both composite materials are non-cytotoxic and degradable.

This study provides a direction of the formulation of environment-friendly resin composite for DLP 3D printing. Both resin composites have huge potential in tissue engineering applications.

This study aims to examine the efforts of two universities in Taiwan, particularly their engagement in coastal rural communities, and provides insights into the substantial contributions of University Social Responsibility (USR) projects toward achieving the sustainable development goals (SDGs) in rural settings. The objective of this research is to analyze the outcomes of these case projects on the SDGs and, consequently, to propose a theoretical model aimed at enhancing student participation in achieving SDGs through USR programs.

This study adapted the methodology comprising SDGs contribution analysis and participant observation. The SDGs contribution analysis unfolds in three steps. First, the authors conducted evaluation of the 2030 Agenda for Sustainable Development. This step involved a thorough analysis of all 17 SDGs and their respective targets to establish a foundational understanding. Second, analyzed the outcomes of the case projects to examine the specific contributions of case projects toward achieving the SDGs. Third, the information from the preceding steps is analyzed to determine the extent of the case projects’ contributions to the SDGs.

The study proposes a theoretical model to enhance student engagement in achieving SDGs, emphasizing student empowerment, community partnership and robust evaluation methods aligned with SDGs and social impacts. This model could offer guidance for higher education institutions (HEIs) globally on utilizing USR programs to contribute to the SDGs, while simultaneously enriching student learning experiences through practical engagement and empowerment.

This model can be enhanced and validated by applying more rigorous scientific methods. For instance, conducting surveys on students and community participants of events and activities, utilizing a statistically rigorous approach such as pre-post testing, can analyze the effectiveness of these programs on various SDG-related variables (e.g. awareness of SDGs). Additionally, exploring the relationships between the tested variables can be a potential research direction. For instance, examining whether community engagement can positively increase the social impacts of USR projects, or whether student empowerment can enhance community capacity building, are important issues worthy of discovery.

This model emphasizes the pivotal role of student empowerment, advocating for an educational approach that not only enhances students’ proficiency in community development but also potentially shapes their career trajectories, as evidenced by the case projects examined in this study. In essence, this model offers HEIs a structured pathway to enrich student engagement in realizing SDGs through USR initiatives. It posits student empowerment as the foundational element, fostering a learning environment where students gain valuable skills and insights into community development, potentially guiding their future professional endeavors. This research provides practical direction for those HEIs implementing USR projects, which will increase the positive impacts brought by HEIs, especially for the students and local community.

To the best of the authors’ knowledge, no previous studies have proposed a theoretical model specifically designed to engage students in achieving SDGs through USR programs in a rural context. The significance of this study lies in its potential to serve as a guide for higher education institutions globally, enabling them to effectively leverage USR programs to contribute toward SDGs. This makes the study an invaluable resource for researchers, policymakers and educators who are committed to fostering sustainability.

This study aims to propose an integrated view and emphasize the importance of bank intangible value binding in customers' robo-advisory adoption. It explores the relationship between robo-advisors and traditional banking and defines the role of bank intangible assets value. It also attempts to understand if trust in the banking institution and the financial consultant determines the effect of these relationships.

The target sample of the study was investors who currently use wealth management services. This study collected 228 valid questionnaires and then executed structural equation model analysis to test the hypotheses.

Results showed that intangible value bindings play a mediating role, which positively affects consumers' willingness to adopt robo-advisors. Consumers' trust in banks and financial consultants are antecedent variables, which positively affect the intangible value bindings between consumers and banks. In addition, when the consumers' investment amount is higher, it will weaken the positive relationship between the intangible value binding and robo-advisor adoption intention.

Most of the past studies have focused on whether robo-advisors would replace personal financial consultants. This study proposes a hybrid model that contains both robo-advisors and traditional banking services, which encourage the acceptance of robo-advisors.

During COVID-19 restrictions, people spent more time in cyberspace and consuming health-related information. An increase was also observed in mediated caring messages or health-relevant information sent to one another. This study aims to explore how the information and interactions around COVID-19 can provide a good learning opportunity for public health, specifically related to eHealth literacy and eHealth promotion.

While mainstream literature has concentrated on experimental designs and a priming effect, this study inspects psychological distance related to a health threat under real-life circumstances. The article adopted a survey approach and utilized PLS-SEM techniques to examine the proposed hypotheses.

Results indicated that whereas closer social support correlates with closer psychological distance and less usage of the social media approach, more substantial COVID-19 impacts were associated with closer psychological distance but greater use of social media. Since both closer psychological distance and social media approach contribute to eHealth literacy, social support from closer and virtual social networks should be embraced but utilized through different routes and for different purposes. The timing of messages but not psychological distance affects people's social media approach, indicating that morning messages should be employed. Moreover, eHealth literacy mediates timing preferences and leads to a preference for eHealth communication earlier in the day. Overall, morning messages create a virtuous circle during a health crisis.

This paper establishes a mechanism of virtuous cycles for eHealth communication during a health threat. Additionally, it bridges existing research gaps by expanding chronopsychology and CLT in the health domain using an empirical approach, a real-life case and an extension of performance regarding information-seeking and utilization.

The China-plus-one strategy is an increasingly attractive supply chain risk management strategy and has been adopted by many multinational enterprises. However, relevant research remains limited and warrants empirical validation. This paper addresses this research gap by investigating the determinants of emerging multinational enterprises’ adoption of a China-plus-one strategy.

The China-plus-one adoption decision of 1,527 firms was predicted using a logistic model based on Taiwan’s official data – Investigation of Foreign Sales and Manufacturing, for the years 2020–2022. This database is administered by the Department of Statistics of the Ministry of Economic Affairs (DSMEA) in Taiwan. Analysis was conducted using SPSS 25.0.

It is suggested that customer pressure and supplier relocation, functioning as push forces, lead to the China-plus-one strategy adopted by Taiwanese firms. Regarding pull forces, lower production cost has a positive association with China-plus-one adoption, whereas sufficient local workforce supply does not have a significant effect. Finally, in terms of the mooring forces, local sales performance is negatively related to the strategy adoption, whereas local access to components shows a positive association with such strategy.

This research uniquely adopts the push–pull–mooring framework to examine factors affecting supply chain restructuring in international business, representing a novel domain for this framework.

Although recent models of place branding have proposed culture as a crucial element in establishing a strong place or nation brand, the way in which cultural products influence the brand equity of other products from the same nation has not yet been studied. This study aims to argue that when a nation has strong legal institutions, as perceived by investors and managers, it offers fertile soil for cultivating cultural products that, when exported, can act as “cultural ambassadors,” promoting the country image in the minds of consumers and the value of the country's brands.

Exports of cultural products are provided by UNESCO. Valuable brands are those that brand finance included in its global top 500 most valuable brands list. The rule of law is provided by the World Bank. Panel regression models are used.

Supporting the hypotheses, exports of cultural products show positive effects on the value of brands from that country, and the rule of law shows positive effects on exports of cultural products.

Policymakers could improve the brand value of local firms by promoting exports of cultural products. To do so, policymakers should initiate judicial reforms that strengthen the rule of law to protect contracts and property rights.

This study examines the hitherto underexplored effects that a country's cultural product exports have on the brand value of firms from that country. Most prior research has focused on factors affecting imports of cultural products.

Riding on the wave of intelligent transportation systems, the vehicular ad hoc network (VANET) is becoming a popular research topic. VANET is designed to build an environment where the vehicles can exchange information about the traffic conditions or vehicle situation to help the vehicles avoid traffic accidents or traffic jams. In order to keep the privacy of vehicles, the vehicles must be anonymous and the routing must be untraceable while still being able to be verified as legal entities. The paper aims to discuss these issues.

The exchanged messages must be authenticated to be genuine and verified that they were sent by a legal vehicle. The vehicles also can mutually trust and communicate confidentially. In VANETs, road-side units (RSUs) are installed to help the vehicles to obtain message authentication or communicate confidentially. However, the coverage of RSUs is limited due to the high cost of wide area installation. Therefore the vehicles must be able to obtain message authentication by themselves – without an RSU.

The authors take the concept of random key pre-distribution used in wireless sensor networks, modify it into a random secret pre-distribution, and integrate it with identity-based cryptography to make anonymous message authentication and private communication easier and safer. The authors construct a two-tier structure. The tier 1, trust authority, assigns n anonymous identities and embeds n secrets into these identities to be the private secret keys for the tier 2, registered vehicles. At any time, the vehicles can randomly choose one of n anonymous identities to obtain message authentication or communicate confidentially with other vehicles.

The processes of building neighbor set, setting pairing value, and message authenticating are proposed in this paper. The proposed method can protect against the attacks of compromising, masquerading, forging, and replying, and can also achieve the security requirements of VANET in message authentication, confidential communication, anonymity, and un-traceability. The performance of the proposed method is superior to the related works.