Search results

With an increase in the amount of multilingual content on the World Wide Web, users are often striving to access information provided in a language of which they are non-native speakers. The purpose of this paper is to present a comprehensive study of user profile representation techniques and investigate their use in personalized cross-language information retrieval (CLIR) systems through the means of personalized query expansion.

The user profiles consist of weighted terms computed by using frequency-based methods such as tf-idf and BM25, as well as various latent semantic models trained on monolingual documents and cross-lingual comparable documents. This paper also proposes an automatic evaluation method for comparing various user profile generation techniques and query expansion methods.

Experimental results suggest that latent semantic-weighted user profile representation techniques are superior to frequency-based methods, and are particularly suitable for users with a sufficient amount of historical data. The study also confirmed that user profiles represented by latent semantic models trained on a cross-lingual level gained better performance than the models trained on a monolingual level.

Previous studies on personalized information retrieval systems have primarily investigated user profiles and personalization strategies on a monolingual level. The effect of utilizing such monolingual profiles for personalized CLIR remains unclear. The current study fills the gap by a comprehensive study of user profile representation for personalized CLIR and a novel personalized CLIR evaluation methodology to ensure repeatable and controlled experiments can be conducted.

The miniscule wireless sensor nodes, engaged in the wide range of applications for its capability of monitoring the physical changes around, requires an improved routing strategy with the befitting sensor node arrangement that plays a vital part in ensuring a completeness of the network coverage.

This paves way for the reduced energy consumption, the enhanced network connections and network longevity. The conventional methods and the evolutionary algorithms developed for arranging of the node ended with the less effectiveness and early convergence with the local optimum respectively.

The paper puts forward the befitting arrangement of the sensor nodes, cluster-head selection and the delayless routing using the ant lion (A-L) optimizer to achieve the substantial coverage, connection, the network-longevity and minimized energy consumption.

The further performance analysis of the proposed system is carried out with the simulation using the network simulator-2 and compared with the genetic algorithm and the particle swarm optimization algorithm to substantiate the competence of the proposed routing method using the ant lion optimization.

Carbon nanotube (CNT) thread ' s piezoresisitive strain sensing properties of gauge factor, linearity, hysteresis, consistency, temperature stability, and bandwidth were evaluated. This evaluation was motivated by little information in literature combined with the need to understand these properties for commercial use. The paper aims to discuss these issues.

The study here analyzes as-spun CNT thread built into unidirectional glass fiber composites and mounted onto aluminium beams with epoxy to evaluate strain sensing properties. The analyses utilize known sensor parameter definitions to quantify sensor performance.

CNT thread can provide reliable and robust strain measurements for composite and metallic structures. The strain sensor performance meets or exceeds other strain sensors in performance.

CNT thread ' s piezoresistive effect is not well understood in terms of Poisson ' s ratio and nanotube contact. More research needs to be carried out to better understand this relationship and optimize the sensor thread.

CNT thread can be utilized as a robust strain sensor for composite and metallic structures. It can also be built into composite materials for embedded strain and damage monitoring. By monitoring composite materials with the sensor thread, reliability will significantly increase. In turn, this will lower safety factors and revolutionize inspection methods for composite materials.

This paper is the first to comprehensively evaluate key strain sensing properties of CNT thread. With all this strain sensor information in one spot, this should help expedite the use of this technology in other research and industry.

Interpersonal interaction can influence consumers’ purchase intention in social commerce (s-commerce). This paper aims to identify interpersonal interaction factors as well as the mediating effect of relationship quality between interpersonal interaction factors and consumers’ purchase intention in s-commerce.

This study explores new dimensions of interpersonal interaction in s-commerce by integrating interaction between consumers and online vendors and that between consumers and online recommenders in s-commerce. An online questionnaire was used to collect the data, and partial least squares structural equation modeling (PLS-SEM) was employed for data analysis.

The results indicate that interpersonal interaction factors of both online vendors and online recommenders positively affect swift guanxi and initial trust between consumers and online vendors. Swift guanxi and initial trust positively affect consumers’ purchase intention. Initial trust partially mediates between interpersonal interaction factors and purchase intention while swift guanxi does not mediate between perceived similarity of online recommenders and purchase intention.

The findings can be used to guide vendors in s-commerce platforms to make good use of platform features to improve interpersonal interaction. Meanwhile, s-commerce platforms should be enhanced with efficient interaction tools to help cultivate relationship quality between consumers and online vendors.

This study combines social exchange theory, trust transfer theory and relationship quality theory to investigate the factors that influence swift guanxi and initial trust between consumers and online vendors, which extends the study of interpersonal interaction and enriches the dimensions of relationship quality in the context of s-commerce.

This research aims to investigate effect of consumer creativity on their evaluations of brands. Consumers’ creative participation is often used by online retailers as a promotional tool nowadays. The authors propose that consumer creativity exerts a positive impact on brand attitudes by affecting their attitudes toward the creative activity itself. Furthermore, consumer creativity moderates the effect of consumers’ perceived level of fit on their acceptance of brand extensions, such that creative consumers will show a higher level of acceptance of distant brand extensions.

The authors test their hypotheses in three laboratory experiments. Study 1 examines the effect of consumer creativity on brand evaluations. Study 2 explores the moderating effect of consumer creativity on perceived level of fit on acceptance of brand extensions. Study 3 replicates the authors findings in Studies 1 and 2 using a better representative sample and a different type of creative task.

Study 1 finds that consumer creativity results in a positive attitude toward brand; this effect is mediated by attitude toward the creative activity. Study 2 shows that creativity leads to a greater level of brand acceptance when the brand extension has a low fit with the focal brand. Study 3 further provides evidence of proposed effects using a different type of creative task with a more representative sample.

In the experiments, this study examined three types of online creative marketing communication activities. Future research could examine other types of consumer creative activities so as to enhance the generalizability of the findings.

Our results provide important implications for firms that intend to exploit the promises of online creativity-themed marketing communications. First, because consumers’ attitudes toward the focal brand hinge on their attitudes toward the creative activity, it is important that firms design their creativity-themed activities carefully, so that they are attractive to the users. Second, firms can exploit the creativity edge by launching new brand extensions that target creative consumers. This effect is even more pronounced when the brand extension exhibits a low fit with the focal brand. These guidelines suggest that firms’ investments in online creativity-themed marketing communications can pay off in terms of improved consumers’ attitudes toward the firms’ brands and brand extensions.

This research makes several theoretical contributions. First, the authors explore the important role of creativity in the context of brand attitudes and brand extensions. This study adds to extant consumer creativity literature by documenting the consequences of consumer creativity in terms of positive outcomes for firms. Second, by examining the mediating effect of attitude toward the creativity task, the authors broaden the scope of attitude-toward-the-site and attitude-toward-the-sponsorship-event research to the online marketing communications setting. Third, by showing that consumer creativity can facilitate the acceptance of distant brand extensions, this study also enriches extant brand extension literature.

At present, teaching methods based on 2D drawings are still commonly used for educating students on the location of steel reinforcement bars in concrete. However, traditional teaching methods have limitations as students can find it difficult to understand 2D drawings. This study aims to develop an interactive and collaborative augmented reality environment (ICARE) using augmented reality (AR) technology to improve students' engagement in learning.

This study develops an ICARE prototype, which is organized into two stages: (1) The augmented teaching environment comprising of models and interactive components; (2) The AR collaborative application which uses Photon Unity Networking (PUN) plugin and Azure spatial anchors cloud service. The AR-based teaching environment runs with Universal Windows Platform (UWP) to enable development in the HoloLens 2 through Microsoft Visual Studio.

An experimental study was conducted, where 60 students were divided into three groups employing Drawings-based, building information modeling (BIM)-based and AR-based methods for teaching. After the test, the three groups of students were requested to complete a questionnaire. According to the analysis of the experimental results, the ICARE can improve students' comprehension, memory of learned materials and their ability to read and understand steel reinforcement drawings improving the quality of teaching, especially interactivity and engagement.

As illustrated in the experiments, the developed ICARE has outstanding performance over conventional approaches in civil engineering courses that can improve students' comprehension and memory of knowledge and their ability to read and understand steel bar drawings. This study provides empirical evidence that AR is a promising technology that can be integrated with traditional classroom instruction and can improve students' comprehension and memory of knowledge and their ability to read and understand steel bar drawings.

The purpose of this paper is to obtain more accurate matching between the request and the release of web service.

This paper adopts Levenshtein distance algorithm to calculate the name similarity between publishing service and request service, employs cosine theorem to compute the text similarity, and uses semantic distance to count the input‐output similarity, then filters out the low similarity and bad reputation services to structure the candidate service set.

The qualitative and quantitative analysis of the scheme is given in this paper. The experimental results show that the multi‐level matching filtering algorithm can obviously improve the recall ratio and precision ratio of web service discovery.

This paper proposes a similarity‐based filtering algorithm for multi‐level matching.

This study aims to focus on the clothing recycling supply chain and aims to provide optimal decisions and managerial insights into supply chain strategies, thereby facilitating the sustainable development of the clothing industry.

Based on previous single- and dual-channel studies, game theory was employed to analyze multiple recycling channels. Concurrently, clothing consumer types were integrated into the analytical models to observe their impact on supply chain strategies. Three market scenarios were modeled for comparative analysis, and numerical experiments were conducted.

The intervention of fashion retailers in the clothing recycling market has intensified competition across the entire market. The proportions of various consumer types, their preferences for online platforms and their preference for the retailer’s channel influence the optimal decisions and profits of supply chain members. The diversity of recycling channels may enhance the recycling volume of clothes; however, it should meet certain conditions.

This study extends the existing theory from a channel dimension by exploring multiple channels. Furthermore, by investigating the classifications of clothing consumers and their influence on supply chain strategies, the theory is enhanced from the consumer perspective.

With the gradual decline of the small retail sector in the past recent years, few researchers have been addressing the issue from a motivational approach. This paper aimed to examine the role of utilitarian, hedonic and ethical motives in the process of forming consumer loyalty in a retail setting.

A total of 213 surveys were carried out among regular fashion and accessories shoppers in Spanish small-sized retailers. A two-step methodology proposed by Anderson and Gerbing (1988) was applied to test the model.

Ethical shopping motivation was found to have the most relevant impact on its perceived quality and on its reassurance to a small-sized retailer, as it represented a strategic asset. Although the most appropriate approach would not be focused mainly on ethical aspects in order to be competitive in the new retailing landscape, consumers should recognize that they are contributing to a worthy cause while enjoying the shopping experience.

Small-sized retailers should provide consumers with good reasons for shopping in their businesses rather than their competitors’. Moreover, it is key to differentiate and build customer loyalty with the purpose of becoming more competitive. As a consequence, in this paper, we propose a measurement scale that can be used to evaluate abstract and complex consumers’ shopping motivations.

The pursuit of more precise knowledge of factors that lead consumers to shop for a specific product is vital for small-sized retailers, toward sustainable competitiveness. Here we analyzed the impact of the three innovative dimensions in shopping motivation on consumers’ perceived quality and their influence on repurchase intention.

The purpose of this paper is to evaluate doctoral candidates’ innovative ability tendency.

This study uses the theory of gray target contribution to analyze the influence degree of doctoral candidates’ individual personality factor toward their innovative ability and calculate gray impact quantitative values.

Based on the theory of contribution degree of gray target, a nine-factor model of innovative personality of doctoral candidates is built. IP=f (B, H, G, Q1, Q2, A, I, F, O), (therein: B – intelligence, H – social boldness, G – perseverance, Q1 – experimental, Q2 – independence, A – gregariousness, I – sensibility, F – excitability, O – anxiety).

This study based on gray target contribution theory builds nine-factor doctoral candidates’ innovative personality model to test the innovative ability tendency of doctoral candidates, which makes cultivating units, mentors and doctoral candidates to know their innovative ability tendency well, perfecting their own knowledge structure in time, effectively improving their innovative ability. The system can also be applied to the work of doctoral candidates as a reference tool to evaluate the innovative ability of applicants.

This study quantitatively evaluates the influence of doctoral candidates’ personality index on the tendency of doctoral candidates’ innovative ability.