Shuo Xu

• Ph.D
• Beijing University of Technology

Based on the self-determination theory (SDT), this evaluates the effects of generative artificial intelligence (Gen-AI) on learning performance within China's education sector, emphasizing the roles of social interaction, utilitarian benefit, knowledge acquisition, and epistemic curiosity. The study employs a dual method, using PLS-SEM and fsQCA ap...

Purpose This study emphasizes digitalization in entrepreneurial ecosystems, fostering sustainability and redefining how businesses operate and entrepreneurs innovate. This study aims to examine trends and key contributions to digitalization in entrepreneurial ecosystems, focusing on organizational cultures and their influence. Design/methodology/a...

The arrival of generative artificial intelligence (GAI) technologies marks a significant transformation in the educational landscape, with implications for teaching and learning performance. These technologies can generate content, simulate interactions, and adapt to learners' needs, offering opportunities for interactive learning experiences. In C...

The rapid advancement of generative artificial intelligence (GAI) and the extensive use of social media have transformed how students engage with educational materials and interact with their peers. Collaborative learning (CL) platforms, empowered by artificial intelligence (AI) algorithms, have gained popularity due to their potential to enhance l...

International entrepreneurship is key to creating business value and advancing sustainable development goals (SDGs) globally at the crossroads of business acumen, innovative thinking, and the ever-growing reach of technology. This study examines how different factors of international entrepreneurship influence the sustainable development of organiz...

Interdisciplinary research teams are crucial in solving complex problems by providing creative solutions that single-discipline teams cannot achieve. Despite considerable research has been conducted to enhance the efficacy of interdisciplinary teams, there is still a lack of understanding regarding the correlation between team diversity and innovat...

The ever-increasing volume of COVID-19-related articles presents a significant challenge for the manual curation and multilabel topic classification of LitCovid. For this purpose, a novel multilabel topic classification framework is developed in this study, which considers both the correlation and imbalance of topic labels, while empowering the pre...

The adoption of generative artificial intelligence (GAI) tools, such as ChatGPT, in higher education presents numerous opportunities and challenges. The use of GAI technologies in various fields, including education, has accelerated as technology develops. The widely used language model ChatGPT, developed by OpenAI, has become progressively more im...

Due to organizations’ unsatisfactory and ineffective environmental performance, scholars focused on employee behavioral improvements rather than relying primarily on technological advancements. This study intended the role of strategic HR practices toward talent retention through job satisfaction and employee work engagement in Pakistan’s education...

Artificial Intelligence (AI) technologies have rapidly transformed the education sector and affect student learning performance, particularly in China, a burgeoning educational landscape. The development of generative artificial intelligence (AI) based technologies, such as chatbots and large language models (LLMs) like ChatGPT, has completely chan...

As technology continues to advance, the integration of generative artificial intelligence tools in various sectors, including education, has gained momentum. ChatGPT, an extensively recognized language model created by OpenAI, has gained significant importance, particularly in education. This study investigates the awareness, acceptance, and adopti...

The context of education has changed due to revolutionary developments in the information communication technology (ICT) industry in the post-COVID era. Innovative learning methods were introduced in the education sector to promote quality education. The students find it more convenient to use ICT tools to integrate their knowledge-seeking. China h...

Purpose Many science, technology and innovation (STI) resources are attached with several different labels. To assign automatically the resulting labels to an interested instance, many approaches with good performance on the benchmark datasets have been proposed for multilabel classification task in the literature. Furthermore, several open-source...

Based on the stimulus organism theory (S-O-R), the current study examines how the chatbot service quality influences e-brand loyalty among luxury fashion brand users and their adoption of it. In the current study, stimuli represent the chatbot service quality and chatbot awareness, prompting positive and negative emotional responses among Chinese u...

The advancement of artificial intelligence (AI) and the ubiquity of social media have become transformative agents in contemporary educational ecosystems. The spotlight of this inquiry focuses on the nexus between AI and social media usage in relation to academic performance and mental well-being, and the role of smart learning in facilitating thes...

Information and communication technology (ICT) has become increasingly important worldwide in education. This study aims to recognize the factors that influence the intention to use information and communication technology (ITUICT) and its acceptance in the education sector in China. A literature review was conducted to ascertain the potential fact...

Super‐partnerships exist between scholars connected within densely‐knit collaboration networks. Understanding how such relationships affect scholars' careers is of great importance. In this paper, focusing on the longitudinal aspects of scientific collaboration, we analyze collaboration profiles from the egocentric perspective and use analytic extr...

Cryptocurrencies—i.e., digital or virtual currencies secured by cryptography based on blockchain technology, such as Bitcoin and Ethereum—have brought transformative changes to the global economic landscape. These innovative transaction methods have rapidly made their mark in the financial sector, reshaping the dynamics of the global economy. Howev...

Given the significance of technology convergence for innovation and launching new products, accurately predicting technology convergence is critical to the pursuit of technological innovation. Although previous studies have been proposed to predict technology convergence, the framework using single-layer IPC networks neglects the potential connecti...

5G technology continues to evolve, and its potential to revolutionize various aspects of society is becoming increasingly evident. However, the successful adoption and utilization of 5G technology depends on various factors, particularly among consumers expected to be early adopters and critical drivers of technological advancements. This study inv...

Gamification entails integrating game design elements, including rewards, points, competition, and interactive challenges, into non-game contexts to engage and motivate individuals. In the context of green consumption, gamification can encourage individuals to acquire more sustainable consumption behaviors. The proposed study aims to examine the in...

This research study aims to reveal the role of supply chain parameters approved by blockchain technology toward firm performance through trust. This study has also examined the moderating role of government support between trust and firm performance. The underlying theories reinforce the usefulness and flexibility of a supply chain in regulating da...

Artificial intelligence (AI) is rapidly transforming the way human resources (HR) functions are carried out in the health sector of China. This study aims to scrutinize the impact of artificial intelligence on the human resource functions operating in the healthcare sector through technological awareness, social media influence, and personal innova...

As worldwide unemployment is an extensive problem with the increasing population every day, job opportunities did not increase with a similar ratio. Unemployment is increasing, affecting developing countries’ economies like Pakistan. This attempt to solve this problem is commonly acknowledged by creating new opportunities and starting new business...

As worldwide unemployment is an extensive problem by the increasing population every day but opportunities for jobs didn’t increase with the similar ratio. Unemployment is increasing, affecting developing countries’ economies like Pakistan. This attempt to solve this problem is commonly acknowledged by creating new opportunities and starting new bu...

Tie strength has been examined as an antecedent of creativity. Although it has been discovered that international collaboration affects scientific performance, the effect of tie strength in the international collaboration network has been largely neglected. Based on international publications of 72 countries/regions published from 1993 to 2013, we...

Academic inventors bridge science and technology, and have attracted increasing attention. However, little is known about whether they have more diverse research interests than researchers with a single role, and whether their important position for science–technology interactions correlates with their diverse interests. For this purpose, we descri...

Authorship credit allocation schemes have attracted considerable research attention. However, no consensus about which one is the best has been attained until now, and limited evidence from practical tasks has been reported. Therefore, this study uses the author interest discovery task as a real-world task case to provide valuable insights into aut...

Under the background of innovation-driven knowledge economy globalization, comprehensive and insightful patent technology information mining can help enterprises win the first-mover advantage in the increasingly fierce technology competition. However, existing machine learning-based methods do not entirely incorporate the characteristics of patent...

To build a full picture of previous studies on the origins of SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2), this paper exploits an active learning-based approach to screen scholarly articles about the origins of SARS-CoV-2 from many scientific publications. In more detail, six seed articles were utilized to manually curate 170 relev...

Purpose The purpose of this study is to solve the problems caused by the growing volumes of pre-annotated literature and variety-oriented annotations, including teamwork, quality control and time effort. Design/methodology/approach An annotation collaboration workbench is developed, which is named as Bureau for Rapid Annotation Tool (Brat). Main f...

The coronavirus disease 2019 (COVID-19) pandemic has been severely impacting global society since December 2019. The related findings such as vaccine and drug development have been reported in biomedical literature—at a rate of about 10 000 articles on COVID-19 per month. Such rapid growth significantly challenges manual curation and interpretation...

The deep learning has become an important technique for semantic relation classification in patent texts. Previous studies just borrowed the relevant models from generic texts to patent texts while keeping structure of the models unchanged. Due to significant distinctions between patent texts and generic ones, this enables the performance of these...

As a widely used technique for discovering developmental trajectory of a specific field of science and technology, main path analysis armed with global search strategy prefers longer citation paths rather than shorter ones. An obvious feature of longer main paths is that the theme of documents may not be so coherent, though longer paths may provide...

The COVID-19 pandemic has been severely impacting global society since December 2019. Massive research has been undertaken to understand the characteristics of the virus and design vaccines and drugs. The related findings have been reported in biomedical literature at a rate of about 10,000 articles on COVID-19 per month. Such rapid growth signific...

Main Path Analysis (MPA) is widely used to trace the developmental trajectory of a technological field through a citation network. The citation-based traversal weight is usually utilized to cherry-pick the most significant path. However, the theme of documents along a main path may not be so coherent, and it is very possible to miss the main paths...

Given that citations are not equally important, various techniques have been presented to identify important citations on the basis of supervised machine learning models. However, only a small volume of instances have been annotated manually with the labels. To make full use of unlabeled instances and promote the identification performance, the sem...

Scientific publications and patents are usually viewed as respective proxies of scientific research and technical development. There is considerable effort spent towards establishing topic linkages between science and technology with the lexical- or topic-based approaches. However, due to the heterogeneity between scholarly articles and patents in...

It seems have become a common practice for the editorial board members to publish the publications in their “own” journals. In view of the important position of the board members, this article devotes to exploiting the difference of the publications by board and non-board members from the perspectives of publication delay and influence. The Journal...

Patent similarity measurement, as one of the fundamental building blocks for patent analysis, is able to derive technical intelligence efficiently, but also can detect the risk of infringement and evaluate whether the invention meets the criteria of novelty and innovation. However, traditional approaches make implicitly several assumptions, such as...

The author interest discovery can help personalized academic recommendation systems. However, many topic models for discovering author interest implicitly assume equal contribution from each coauthor to a target document. To loosen this limitation, a novel model, ATcredit, is proposed to strengthen the Author-Topic (AT) model with an authorship cre...

Although the citations between scientific documents are deemed as a vehicle for dissemination, inheritance and development of scientific knowledge, not all citations are well-positioned to be equal. A plethora of taxonomies and machine-learning models have been implemented to tackle the task of citation function and importance classification from q...

The identification of emerging technologies can bring valuable intelligence to enterprises and countries determining research and development (R&D) priorities. Emerging technologies are closely related to emerging topics in terms of several well-documented attributes: relatively fast growth, radical novelty and prominent impact. Our previous work o...

Against the backdrop of globalization, the world is witnessing increasingly frequent transnational mobility, placing scientific mobility in the spotlight. Highly competitive researchers with an international vision are regarded as engines that, for any nation, drive scientific and technological progress and social development. Over the past two dec...

Information extraction is the fundamental technique for text-based patent analysis in era of big data. However, the specialty of patent text enables the performance of general information-extraction methods to reduce noticeably. To solve this problem, an in-depth exploration has to be done for clarify the particularity in patent information extract...

The text-based patent analysis is grounded in information extraction technique. However, such technique suffers from obvious defects such as low degree of automation and unsatisfactory extraction accuracy. To deal with these problems, after an information schema is pre-defined, which contains 17 types of entities and 15 types of semantic relations,...

The arrival of information age provides a platform for the development of academic field. Knowledge exchanges between disciplines are becoming more frequent, boundaries are gradually blurred, interdisciplinary has become an inevitable trend. In the field of Scientometrics, it has become a new hotspot to study the interdisciplinarity of specific doc...

Purpose Image classification is becoming a supporting technology in several image-processing tasks. Due to rich semantic information contained in the images, it is very popular for an image to have several labels or tags. This paper aims to develop a novel multi-label classification approach with superior performance. Design/methodology/approach M...

The fast development of the emerging research topics field results in hundreds of theoretical and empirical publications. However, to our knowledge, there is no comprehensive and objective literature review on this field until now. To this end, a citation network consisting of 1607 papers between 1965 and early 2019 is explored to discover the know...

Emerging research topic detection can benefit the research foundations and policy-makers. With the long-term and recent interest in detecting emerging research topics, various approaches are proposed in the literature. Though, there is still a lack of well-established linkages between the clear conceptual definition of emerging research topics and...

Constructing academic networks to explore intellectual structure realize academic community detection, which can promote scientific research innovation and discipline progress, constitutes an important research topic. In this study, tripartite citation is fused with co-citation and coupling relations as a way of weighting the strength of direct cit...

Though the bibliographic databases, such as Web of Science (WoS), largely promote the development of scientometrics and informetrics, these databases are not free of errors. The main purpose of this work is to figure out which types of DOI errors of cited references exist, how often each type of errors occur, and whether it is possible to automatic...

It is increasingly important to build topic linkages between scientific publications and patents for the purpose of understanding the relationships between science and technology. Previous studies on the linkages mainly focus on the analysis of nonpatent references on the front page of patents, or the resulting citation‐link networks, but with unsa...

Western China serves as a significant national ecological security barrier, but the eco-environment is deteriorating. The government of China has been making great efforts to reduce the loss of soil, improve water retention, and generally protect biodiversity and eco-systems in western China by implementing several large-scale forestry and environm...

Semantic relation extraction is a crucial step of automatically constructing a knowledge graph from unstructured biomedical text. Many real-world applications can benefit from it. As unsupervised relation extraction approaches, generative probabilistic models, Rel-LDA and Type-LDA, are receiving more attention in recent years. However, these two mo...

It is increasing important to identify automatically thematic structures from massive scientific literature. The interdisciplinarity enables thematic structures without natural boundaries. In this work, the identification of thematic structures is regarded as an overlapping community detection problem from the large-scale citation-link network. A m...

Text classification is the task of assigning predefined classes to free-text documents, and it can provide conceptual views of document collections. The multinomial naïve Bayes (NB) classifier is one NB classifier variant, and it is often used as a baseline in text classification. However, multinomial NB classifier is not fully Bayesian. This study...

Author name disambiguation is an important problem that needs to be resolved in bibliometric analysis or tech mining. Many techniques have been presented; however, most of them require a long run time or additional information. A new method based on semantic fingerprints was presented to disambiguate author names without external data. A manually a...

This book constitutes the refereed proceedings of the 13th Information Retrieval Societies Conference, AIRS 2017, held in Jeju, Korea, in November 2017. The 17 full papers presented were carefully reviewed and selected from numerous submissions. The final program of AIRS 2017 is divided in the following tracks: IR Infrastructure and Systems; IR Mo...

Text classification is the task of assigning predefined categories to natural language documents, and it can provide conceptual views of document collections. The Naïve Bayes (NB) classifier is a family of simple probabilistic classifiers based on a common assumption that all features are independent of each other, given the category variable, and...

Clustering analysis seeks to partition a given dataset into groups or clusters so that the data objects within a cluster are more similar to each other than the objects in different clusters. A very rich literature on clustering analysis has developed over the past three decades. But a crucial question still remains unanswered: how many clusters ar...

The automatic extraction of chemical information from text requires the recognition of chemical entity mentions as one of its key steps. When developing supervised named entity recognition (NER) systems, the availability of a large, manually annotated text corpus is desirable. Furthermore, large corpora permit the robust evaluation and comparison o...

The paper aims to discover overlapping communities and their research interests in academic social network. The network is constructed based on co-authorships. Cliques are extracted to discover overlapping communities. Keywords used by authors in communities are counted and sorted, and top N keywords are selected to represent their research interes...

A social network service (SNS) is a platform to build social networks or social relations among people. Many users enjoy SNS with their smart devices, which are mostly equipped with sensory devices. The sensitive information produced by these sensory devices is uploaded to SNS, which may raise many potential risks. In order to share one's sensitive...

In order to improve the quality of applications, such as recommendation or retrieval in knowledge-based service system, it is very helpful to uncover research topics of academic communities in scientific collaboration network (SCN). Previous research mainly focuses on network characteristics measurement and community evolution, but it remains large...

One of the key issues for providing users user-customized or context-aware services is to automatically detect latent topics, users' interests, and their changing patterns from large-scale social network information. Most of the current methods are devoted either to discovering static latent topics and users' interests or to analyzing topic evoluti...

One of the key problems in upgrading information services towards knowledge services is to automatically mine latent topics, users' interests and their evolution patterns from large-scale S&T literatures. Most of current methods are devoted to either discover static latent topics and users' interests, or to analyze topic evolution only from intra-f...

Patents are one of the most important innovative resources. It is a challenge and useful to discover technical topics and their relations from patents. A process framework is proposed to mine technical topics and construct their relation network from Chinese patents. The process consists of four stages. First, technical terms are extracted from pat...

Inspired by the hierarchical Dirichlet process (HDP), we present a generalized coAT (coauthor Topic) model, also called infinite coAT model, in this paper. The infinite coAT model is a non-parametric extension of the coAT model. And this model can automatically determine the number of topics which are regarded for the probabilistic distribution of...

In recent, business intelligence becomes one of important issues due to various analyses on technology trends. Especially, understanding the relations and influences between technologies is core property for the high-performed analysis. To do this, a few works have utilized ontologies constructed automatically but still have many errors and it caus...

Analysis, prediction, and recommendation of information about experts are very important tasks for future research planning and strategy establishment. However, it takes much time and efforts even for precise analysis of experts because we need to analyze huge and diverse heterogeneous information. There are several application and tools for suppor...

A Chinese Diseases Question Answering System(Hestia QA) is being developed by ISTIC. As a part of Hestia QA, a XML-based document retrieval and similarity calculation model is established here. The texts which describe diseases in Chinese are indexed and wrapped in XML tags. The query is compared with related tags in XML document and the similarity...

Recently, there is an increasing interest in effectively using big data. It is also thought that the machine learning methods are crucial to effectively extract knowledge from big text data when they are coupled with big data technologies such as MapReduce and Hadoop. For tasks such as the knowledge extraction from huge amount of texts and the reas...

The paper aims to use strategic diagram technique to detect research themes and reveal their evolutionary trends in a scientific field using bibliometric data under practical application. Keywords are selected not only from author-provided and machine-indexed keywords, but also extracted from the full text so as to eliminate the “indexer effect”. T...

There are often the underlying cross relatedness amongst multiple tasks, which is discarded directly by traditional single-task learning methods. Since multi-task learning can exploit these relatedness to further improve the performance, it has attracted extensive attention in many domains including multimedia. It has been shown through a meticulou...

In order to improve information access on chemical compounds and drugs (chemical entities) described in text repositories, it is very crucial to be able to identify chemical entity mentions (CEMs) automatically within text. The CHEMDNER challenge in BioCreative IV was specially designed to promote the implementation of corresponding systems that ar...

Following the Internet, the Internet of Things (IoT) becomes a prime vehicle for supporting auction. The use of market mechanisms to solve computer science problems is gaining significant traction. More and more clues show that the bidders tend to be risk-averse ones. However, traditional nonparametric approach is only applicable for the case of ri...

Identification of phosphorylation sites by computational methods is becoming increasingly important because it reduces labor-intensive and costly experiments and can improve our understanding of the common properties and underlying mechanisms of protein phosphorylation. A multitask learning framework for learning four kinase families simultaneously...

Description of selected features from AAIndex. Descriptions of AAIndex records corresponding to selected features in subset 1, 2, 3 and 4.

The next-generation sequencing coupled with chromatin immunoprecipitation (ChIP-seq) is becoming a key technology for the study of transcriptional regulation in the context of functional genomics. Due to the overwhelming amount of data generated from ChIP-seq experiments, the ChIP-seq data processing brings many new challenges in the field of bioin...