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The purpose of this paper is to share knowledge of how annotation can be the basis for knowledge sharing.

The method used was derived from mathematical methods applied to set theory.

It was presented that one document can be easily used for experience sharing with multiple users. Multiple documents will be difficult to use as source of experience sharing.

Experience sharing has never been presented as intersection of annotation, document and users using mathematic principles.

The purpose of this paper is to annotate an attribute of a problem, a solution or no annotation on learners’ opinions automatically for supporting the learners’ discussion without a facilitator. The case method aims at discussing problems and solutions in a target case. However, the learners miss discussing some of problems and solutions.

Because opinions about problems and solutions on the same case are similar to each other, the proposed method uses opinions that are correctly annotated in past discussions for annotating an appropriate attribute on each opinion in discussions of the same case. The annotation on each opinion is identified by Support Vector Machine learned with opinions and annotations in the past discussion.

Compared to a simple method that uses decision tree classification, this proposed method improves the recall rate and the precision rate of annotating the attribute by over 10 per cent. The proposed method is effective for automatic annotation.

Because the recall rate and the precision rate of annotating an attribute of a problem are over 80 per cent, it is possible to make learners aware of problems that they should discuss. On the other hand, the recall rate and the precision rate of annotating an attribute of a solution are still low. The authors discuss the research issue to improve the rates for automatic annotation.

Annotation is a practice that is familiar to many of us, and yet it is a practice so natural that it is hard to pin down its characteristics, to find where its edges are, and identify what it does for us. In this piece, we use reflections on the practices of annotation in four fields of work: academia, software engineering, medical sonography and visual art as a point of departure to theorise annotation as a set of practices that bridge reading, writing and thinking. We think about annotation being performative and consider what and how it brings into being. Revealing hidden practices in our working lives, such as annotation, helps us to understand how knowledge comes to be created, disseminated, legitimated and popularised. To this end, we make the practices of annotation involved in writing the present piece visible in an effort to write differently in management and organisation studies, unpicking and exposing it as ever dialogical and unfinished.

Empirical validation of educational technology is critical for best practice, particularly when courses are delivered online. This study aims to investigate the predictive relationship of usage behaviors on perceptions of 30 preservice special education teachers while reading in an online social annotation reading tool.

In this single-group quasi-experimental study, participants completed two readings in Perusall, once individually and once in small groups, then took a researcher-created survey after each reading. Descriptive data and paired sample t-tests were calculated. Predictive relationships between usage behaviors and survey results were analyzed with linear regression models.

Participants thought Perusall was useful for their learning and easier to use in small groups and that guided reading prompts were helpful. Usage behaviors did not significantly account for participant beliefs about Perusall. Instructors may wish to use guided reading prompts and small groups to maximize student learning and engagement.

This study addresses gaps in the literature (Suhre et al., 2019; Sun et al., 2023) by following one group of students over two semesters, using a commercially available tool, measuring actual usage behaviors and not solely student perceptions and analyzing instructor perceptions of the tool. The authors contribute further evidence that group-constructed knowledge is valuable for undergraduate learning (Kalir et al., 2020b). The authors also provide data-based suggestions for the use of social annotation tools that maximize student learning and engagement.

With the rapid development of technology, 360° panorama on mobile as a very convenient way to present virtual reality has brought a new shopping experience to consumers. Usually, consumers get product information through virtual annotations in 360° panorama and then make a series of shopping behaviors. The visual design of virtual annotation significantly influences users' online visual search for product information. This study aims to investigate the influence of the visual design of virtual annotation on consumers' shopping experience in the online shopping interface of 360° panorama.

A 2 × 3 between-subject design was planned to help explore whether different display model of annotation (i.e. negative polarity and positive polarity) and different background transparency of annotation (i.e. 0% transparency, 25% transparency and 50% transparency) may affect users' task performance and their subjective evaluations.

(1) Virtual annotations with different background transparency affect user performance, and transparency has better visual search performance. (2) Virtual annotation background display mode may affect the user operation performance; the positive polarity of the virtual annotation is more convenient for the users' visual searching for product information. (3) When the annotation background transparency is opaque or semi-transparent, the negative polarity display is more favorable to the users' visual search. However, this situation is reversed when the annotation background transparency is 25%. (4) Participants preferred the presentation of positive polarity virtual annotations. (5) Regarding the degree of willingness to use and ease of understanding, participants preferred the negative polarity display for 0% background transparency or 50% background transparency. However, the opposite result was obtained for 25% background transparency.

The findings generated from the research can be a good reference for the development of virtual annotation visual design for mobile shopping applications.

1. Virtual annotation background transparency and background display mode are two essential attributes of 360° panoramas.

2. This study examined how virtual annotation background transparency and background display mode influence user performance and experience.

3. It is recommended to use a translucent or opaque annotation background with a negative polarity display.

4. Virtual annotation presentation with 25% background transparency facilitates consumer searching and comparison of product information.

5. Users prefer a positive polarity annotation display.

Virtual annotation background transparency and background display mode are two essential attributes of 360° panoramas.

This study examined how virtual annotation background transparency and background display mode influence user performance and experience.

It is recommended to use a translucent or opaque annotation background with a negative polarity display.

Virtual annotation presentation with 25% background transparency facilitates consumer searching and comparison of product information.

Users prefer a positive polarity annotation display.

The purpose of this paper is to propose a methodology for the enrichment and tailoring of a knowledge organization system (KOS), in order to support the information extraction (IE) task for the analysis of documents in the tourism domain. In particular, the KOS is used to develop a named entity recognition (NER) system.

A method to improve and customize an available thesaurus by leveraging documents related to the tourism in Italy is firstly presented. Then, the obtained thesaurus is used to create an annotated NER corpus, exploiting both distant supervision, deep learning and a light human supervision.

The study shows that a customized KOS can effectively support IE tasks when applied to documents belonging to the same domains and types used for its construction. Moreover, it is very useful to support and ease the annotation task using the proposed methodology, allowing to annotate a corpus with a fraction of the effort required for a manual annotation.

The paper explores an alternative use of a KOS, proposing an innovative NER corpus annotation methodology. Moreover, the KOS and the annotated NER data set will be made publicly available.

This paper aims to examine how gender differences influence students’ reactions to the use of the annotatable multimedia e-reader (AME). To reach this aim, we develop an AME where various annotation tools are provided to help students learn English in-class and after-class.

An empirical study was conducted with 63 fifth-grade students from an elementary school. A pre-test and post-test were used to identify their prior knowledge and learning achievement, respectively. A questionnaire was applied to identify participants’ perceptions towards the AME.

The results show that students’ post-test scores are significantly related to after-class behaviour, instead of in-class behaviour. Females prefer to use the text annotation and teachers’ voice, but it is voice annotation that is beneficial to improve their learning achievement. Conversely, males prefer to use the text-to-speech only, but it is text annotation that is helpful to improve their learning achievement. Additionally, the ease of use affects males’ intention to use the AME to learn English after-class while it has no effects on females.

This study not only shows the importance of gender differences but also demonstrates the essence of after-class learning behaviour. More importantly, a framework is proposed to support designers to develop e-readers that can accommodate the preferences of females and males.

The purpose of this paper is to semantically annotate the content of digital images with the use of Semantic Web technologies and thus facilitate retrieval, integration and knowledge discovery.

After a review and comparison of the existing semantic annotation models for images and a deep analysis of the characteristics of the content of images, a multi-dimensional and hierarchical general semantic annotation framework for digital images was proposed. On this basis, taking histories images, advertising images and biomedical images as examples, by integrating the characteristics of images in these specific domains with related domain knowledge, the general semantic annotation framework for digital images was customized to form a domain annotation ontology for the images in a specific domain. The application of semantic annotation of digital images, such as semantic retrieval, visual analysis and semantic reuse, were also explored.

The results showed that the semantic annotation framework for digital images constructed in this paper provided a solution for the semantic organization of the content of images. On this basis, deep knowledge services such as semantic retrieval, visual analysis can be provided.

The semantic annotation framework for digital images can reveal the fine-grained semantics in a multi-dimensional and hierarchical way, which can thus meet the demand for enrichment and retrieval of digital images.

This paper aims to propose a system for the semantic annotation of audio‐visual media objects, which are provided in the documentary domain. It presents the system's architecture, a manual annotation tool, an authoring tool and a search engine for the documentary experts. The paper discusses the merits of a proposed approach of evolving semantic network as the basis for the audio‐visual content description.

The author demonstrates how documentary media can be semantically annotated, and how this information can be used for the retrieval of the documentary media objects. Furthermore, the paper outlines the underlying XML schema‐based content description structures of the proposed system.

Currently, a flexible organization of documentary media content description and the related media data is required. Such an organization requires the adaptable construction in the form of a semantic network. The proposed approach provides semantic structures with the capability to change and grow, allowing an ongoing task‐specific process of inspection and interpretation of source material. The approach also provides technical memory structures (i.e. information nodes), which represent the size, duration, and technical format of the physical audio‐visual material of any media type, such as audio, video and 3D animation.

The proposed approach (architecture) is generic and facilitates the dynamic use of audio‐visual material using links, enabling the connection from multi‐layered information nodes to data on a temporal, spatial and spatial‐temporal level. It enables the semantic connection between information nodes using typed relations, thus structuring the information space on a semantic as well as syntactic level. Since the description of media content holds constant for the associated time interval, the proposed system can handle multiple content descriptions for the same media unit and also handle gaps. The results of this research will be valuable not only for documentary experts but for anyone with a need to manage dynamically audiovisual content in an intelligent way.

An automatic text annotation system (ATAS) that can collect resources from different databases through Linked Data (LD) for automatically annotating ancient texts was developed in this study to support digital humanities research. It allows the humanists referring to resources from diverse databases when interpreting ancient texts as well as provides a friendly text annotation reader for humanists interpreting ancient text through reading. The paper aims to discuss whether the ATAS is helpful to support digital humanities research or not.

Based on the quasi-experimental design, the ATAS developed in this study and MARKUS semi-ATAS were compared whether the significant differences in the reading effectiveness and technology acceptance for supporting humanists interpreting ancient text of the Ming dynasty’s collections existed or not. Additionally, lag sequential analysis was also used to analyze users’ operation behaviors on the ATAS. A semi-structured in-depth interview was also applied to understand users’ opinions and perception of using the ATAS to interpret ancient texts through reading.

The experimental results reveal that the ATAS has higher reading effectiveness than MARKUS semi-ATAS, but not reaching the statistically significant difference. The technology acceptance of the ATAS is significantly higher than that of MARKUS semi-ATAS. Particularly, the function comparison of the two systems shows that the ATAS presents more perceived ease of use on the functions of term search, connection to source websites and adding annotation than MARKUS semi-ATAS. Furthermore, the reading interface of ATAS is simple and understandable and is more suitable for reading than MARKUS semi-ATAS. Among all the considered LD sources, Moedict, which is an online Chinese dictionary, was confirmed as the most helpful one.

This study adopted Jieba Chinese parser to perform the word segmentation process based on a parser lexicon for the Chinese ancient texts of the Ming dynasty’s collections. The accuracy of word segmentation to a lexicon-based Chinese parser is limited due to ignoring the grammar and semantics of ancient texts. Moreover, the original parser lexicon used in Jieba Chinese parser only contains the modern words. This will reduce the accuracy of word segmentation for Chinese ancient texts. The two limitations that affect Jieba Chinese parser to correctly perform the word segmentation process for Chinese ancient texts will significantly affect the effectiveness of using ATAS to support digital humanities research. This study thus proposed a practicable scheme by adding new terms into the parser lexicon based on humanists’ self-judgment to improve the accuracy of word segmentation of Jieba Chinese parser.

Although some digital humanities platforms have been successfully developed to support digital humanities research for humanists, most of them have still not provided a friendly digital reading environment to support humanists on interpreting texts. For this reason, this study developed an ATAS that can automatically retrieve LD sources from different databases on the Internet to supply rich annotation information on reading texts to help humanists interpret texts. This study brings digital humanities research to a new ground.

This study proposed a novel ATAS that can automatically annotate useful information on an ancient text to increase the readability of the ancient text based on LD sources from different databases, thus helping humanists obtain a deeper and broader understanding in the ancient text. Currently, there is no this kind of tool developed for humanists to support digital humanities research.