TERMS: Techniques for electronic resources management

Librarians and information specialists have been finding ways to manage electronic resources for over a decade now. However, much of this work has been an ad hoc and learn-as-you-go process. The literature on electronic resource management shows this work as being segmented into many different areas of traditional librarian roles within the library. In addition, the literature show how management of these resources has driven the development of various management tools in the market as well as serve as the greatest need in the development of next generation library systems. TERMS is an attempt to create a series of on-going and continually developing set of management best practices for electronic resource management in libraries

Motives of Social Media Usage on Building Consumer Behavioural Engagement

Social media plays a pivotal role in the present digitalized business context by reshaping the marketing strategies of business entities by focusing greater level of consumer engagement. The consumer participation in brand building activities has become a mainstream research concern over social media marketing. Despite the different marketing and promotional efforts taken by marketers, recent studies emphasis more on investigating level of consumer engagement within contemporaneous digital platforms. Alongside, this study attempted to investigate the consumer behavioural engagement in social media marketing, and it was conceptualized based on self – determination theory. Accordingly, consumer autonomy, competence, and relatedness were tested with consumer behavioural engagement in social media marketing. Following a deductive method as the approach, a comprehensive literature review was conducted to construct the study hypotheses. Survey method was used to collect data from a sample of 246 undergraduates in both state and private sector higher educational institutes. The analysis was based on both descriptive and inferential analysis, to understand the relationship between key consumer autonomy, competence, and relatedness towards behavioural engagement. Findings reveal that the consumer competence over social media platforms is the most important determinant of one’s self – determination. Further, the behavioural engagement of consumers is highly influenced by consumer relatedness, showing favourable relationships among both community relatedness as well as brand relatedness. Some of the determinants such as self-censorship and privacy concerns were identified as no significant relationship with consumer behavioural engagement. It provided a considerable amount of interesting findings for practitioner for developing effective marketing and promotional campaigns in the context of social media to gain a greater level of consumer behavioural engagement. Finally, the study was concluded with important insights about the consumer behavioural engagement in social media marketing with some recommended practices for higher achievements. Keywords: Autonomy, Self – censorship, Self – Efficacy, Relatedness, Behavioural engagemen

CHORUS Deliverable 3.3: Vision Document - Intermediate version

The goal of the CHORUS vision document is to create a high level vision on audio-visual search engines in order to give guidance to the future R&D work in this area (in line with the mandate of CHORUS as a Coordination Action). This current intermediate draft of the CHORUS vision document (D3.3) is based on the previous CHORUS vision documents D3.1 to D3.2 and on the results of the six CHORUS Think-Tank meetings held in March, September and November 2007 as well as in April, July and October 2008, and on the feedback from other CHORUS events. The outcome of the six Think-Thank meetings will not just be to the benefit of the participants which are stakeholders and experts from academia and industry – CHORUS, as a coordination action of the EC, will feed back the findings (see Summary) to the projects under its purview and, via its website, to the whole community working in the domain of AV content search. A few subjections of this deliverable are to be completed after the eights (and presumably last) Think-Tank meeting in spring 2009

Determinants of social media adoption by B2B organizations

This study contributes to the current dearth of knowledge on the potential of social media as a marketing tool in industrial settings, by focusing on factors that determine social media adoption by B2B organizations. A conceptual model, which draws on the technology acceptance model and resource-based theory, is developed and tested using quantitative data from B2B organizations in the UK. Findings suggest that perceived usefulness of social media within B2B organizational contexts is determined by image, perceived ease of use and perceived barriers. Additionally, the results show that adoption of social media is significantly affected by organizational innovativeness and perceived usefulness. The moderating role of organizational innovativeness is also tested but no support is found. The findings of the study are further validated via nine qualitative interviews with B2B senior managers, yielding additional interesting and in-depth insights into the drivers of social media adoption by B2B organizations

The most valued social media attributes of Portuguese consumers

The exponential growth of the entertainment and media industry has revolutionized the social media landscape. Increasingly more people use social media platforms in their daily lives for different reasons. The goal of this research is, in particular, to determine what are the attributes of Facebook Instagram and Tik Tok they value the most, as well as having an overview on how Portuguese consumers perceive such platformsandwhat influences its engagement. To reach such goals,reasons why people use social media were identified,aperceptual map with two dimensions was plotted, and a conjoint analysis was performed. On the associations found to be linked with social media, all three social media platforms do not need to readjust their positioning strategy to occupy a specific position in the market, but there is still room for attributes improvement, to engage with potential Portuguese valuable consumers, considering the different needs, preferences, and behaviors. The most important feature and counterpart for the usage of social media is linked with privacy concerns

HuggingGPT: Solving AI Tasks with ChatGPT and its Friends in Hugging Face

Solving complicated AI tasks with different domains and modalities is a key step toward artificial general intelligence. While there are numerous AI models available for various domains and modalities, they cannot handle complicated AI tasks autonomously. Considering large language models (LLMs) have exhibited exceptional abilities in language understanding, generation, interaction, and reasoning, we advocate that LLMs could act as a controller to manage existing AI models to solve complicated AI tasks, with language serving as a generic interface to empower this. Based on this philosophy, we present HuggingGPT, an LLM-powered agent that leverages LLMs (e.g., ChatGPT) to connect various AI models in machine learning communities (e.g., Hugging Face) to solve AI tasks. Specifically, we use ChatGPT to conduct task planning when receiving a user request, select models according to their function descriptions available in Hugging Face, execute each subtask with the selected AI model, and summarize the response according to the execution results. By leveraging the strong language capability of ChatGPT and abundant AI models in Hugging Face, HuggingGPT can tackle a wide range of sophisticated AI tasks spanning different modalities and domains and achieve impressive results in language, vision, speech, and other challenging tasks, which paves a new way towards the realization of artificial general intelligence

Determinants of social media adoption by B2B organizations

Determinants of social media adoption by B2B organization

Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluation

This paper surveys the current state of the art in Natural Language Generation (NLG), defined as the task of generating text or speech from non-linguistic input. A survey of NLG is timely in view of the changes that the field has undergone over the past decade or so, especially in relation to new (usually data-driven) methods, as well as new applications of NLG technology. This survey therefore aims to (a) give an up-to-date synthesis of research on the core tasks in NLG and the architectures adopted in which such tasks are organised; (b) highlight a number of relatively recent research topics that have arisen partly as a result of growing synergies between NLG and other areas of artificial intelligence; (c) draw attention to the challenges in NLG evaluation, relating them to similar challenges faced in other areas of Natural Language Processing, with an emphasis on different evaluation methods and the relationships between them.Comment: Published in Journal of AI Research (JAIR), volume 61, pp 75-170. 118 pages, 8 figures, 1 tabl