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The purpose of this paper is to present a framework applicable to interactive video retrieval. The objective of the framework is so that it can be applied conceptually for understanding users and use of video digital libraries, and also practically for designing retrieval components like user interfaces.

The framework was developed through a user-centered and analytical approach, and serves as an initial attempt at generalizing how users interact when searching and browsing digital video, throughout different situations, along with the general designs that can be supportive.

The framework is two-fold, yet, together, comprises one set of conceptual findings. The first component of the framework depicts generalized user interactions throughout varying contexts of an interactive video retrieval process, followed by a second component, an illustration of the resulting supportive interface designs or sets of features. Cautions from previous studies not to over generalize the interactive process were heeded.

The implications for such research are based on the understanding that video retrieval will benefit from the advancement of user-centered foundations, which can guide and support design decisions for resources like digital libraries.

The need for this study is rather straightforward: there is currently not enough conceptual research of interactive video retrieval from a user-centered perspective, which contrasts with other areas of information retrieval research where the interaction process has been thoroughly examined for a variety of domains and contexts with implications for different retrieval tools like OPACs, search engines, and article databases.

This article aims to examine how the interactions and perceptions of users from a defined domain, i.e. science education, vary across different groups of teachers while retrieving video. Given the prevalence of digital resources in use in education today, it is critical to assess users’ perspectives and experiences for retrieving information across different contexts and individual user groups.

Interactive search experiments with 28 users were performed. A pre-experiment questionnaire collected the demographic information used to form groups for comparison in the present study. Users attempted six experimenter-developed topics using a prototype video retrieval system; experimental measures were recorded, including all actions, completion rates, errors and durations. Users rated their experiences and levels of satisfaction with different aspect of the system after each search topic. Data analyses included mean comparisons across the different groups.

A variety of influences emerged from the results, including significant variations among teachers’ interactions, levels of satisfaction and expectations across different groups of users.

Understanding the interactions and perceptions when retrieving digital video provides insights for information professionals on how to better support the needs of different users. If systems are not taking into account users and context, there can be a mismatch between the needs of users and interactive systems, which can lead to low perceptions and further underuse of digital resources.

Although similar influences on digital libraries have been analysed in other contexts, they have not been directly assessed, as they specifically pertain to experiences with and perceptions of video.

Keywords search is intuitive, simple to use and convenient. It is also the de facto input interface for textual and multimedia retrieval. However, individuals often perform poorly when faced with exploratory search tasks that are common during learning, resulting in poor quality searches. The purpose of this paper is to examine how adolescent learners search and select videos to support self-learning. The findings allow for the identification of design concepts of video retrieval interface and features that can facilitate better exploratory searches.

Participants were assigned two customized video search tasks. The think-aloud protocol is used to allow participants to verbalize their actions, thoughts and feeling. This approach offered rich insights to the participants’ cognitive processes and considerations when performing the search tasks.

This study identified five themes for exploratory video search behavior: selection of internet resources, query formulation/reformulation, selection of the video(s) for preview, getting acquainted with the video content, and making a decision for the search task. The analysis of these themes led to a number of design concepts, ranging from supporting exploration of topics to better interaction with metadata.

The findings can inform future development of dedicated video retrieval systems interfaces that seeks to facilitate effective exploratory searches by learners.

This study contributes by suggesting design concepts for video retrieval system developers to support exploratory video searches.

The object of this empirical research study is emotion, as depicted and aroused in videos. This paper seeks to answer the questions: Are users able to index such emotions consistently? Are the users' votes usable for emotional video retrieval?

The authors worked with a controlled vocabulary for nine basic emotions (love, happiness, fun, surprise, desire, sadness, anger, disgust and fear), a slide control for adjusting the emotions' intensity, and the approach of broad folksonomies. Different users tagged the same videos. The test persons had the task of indexing the emotions of 20 videos (reprocessed clips from YouTube). The authors distinguished between emotions which were depicted in the video and those that were evoked in the user. Data were received from 776 participants and a total of 279,360 slide control values were analyzed.

The consistency of the users' votes is very high; the tag distributions for the particular videos' emotions are stable. The final shape of the distributions will be reached by the tagging activities of only very few users (less than 100). By applying the approach of power tags it is possible to separate the pivotal emotions of every document – if indeed there is any feeling at all.

This paper is one of the first steps in the new research area of emotional information retrieval (EmIR). To the authors' knowledge, it is the first research project into the collective indexing of emotions in videos.

Purpose – This paper aims to provide an initial understanding of the constraints that historical video collections pose to video retrieval technology and the potential that online access offers to both archive and users. Design/methodology/approach – A small and unique collection of videos on customs and folklore was used as a case study. Multiple methods were employed to investigate the effectiveness of technology and the modality of user access. Automatic keyframe extraction was tested on the visual content while the audio stream was used for automatic classification of speech and music clips. The user access (search vs browse) was assessed in a controlled user evaluation. A focus group and a survey provided insight on the actual use of the analogue archive. The results of these multiple studies were then compared and integrated (triangulation). Findings – The amateur material challenged automatic techniques for video and audio indexing, thus suggesting that the technology must be tested against the material before deciding on a digitisation strategy. Two user interaction modalities, browsing vs searching, were tested in a user evaluation. Results show users preferred searching, but browsing becomes essential when the search engine fails in matching query and indexed words. Browsing was also valued for serendipitous discovery; however the organisation of the archive was judged cryptic and therefore of limited use. This indicates that the categorisation of an online archive should be thought of in terms of users who might not understand the current classification. The focus group and the survey showed clearly the advantage of online access even when the quality of the video surrogate is poor. The evidence gathered suggests that the creation of a digital version of a video archive requires a rethinking of the collection in terms of the new medium: a new archive should be specially designed to exploit the potential that the digital medium offers. Similarly, users' needs have to be considered before designing the digital library interface, as needs are likely to be different from those imagined. Originality/value – This paper is the first attempt to understand the advantages offered and limitations held by video retrieval technology for small video archives like those often found in special collections.

Data mining is the process of detecting knowledge from a given huge data set. Among the data set, multimedia is the data which contains diverse data such as audio, video, image, text and motion. In this growing field of video data, mining the video data plays vital role in the field of video data mining. In video data mining, video data are grouped into frames. In this vast amount of video frames, the fast retrieval of needed information is important one. This paper aims to propose a Birch-based clustering method for content-based image retrieval.

In image retrieval system, image segmentation plays a very important role. A text file, normally, is divided into sections, that is, piece, sentences, word and character for this information which are organized and indexed effectively like in a video, the information is dynamic in nature and this information is converted to static for easy retrieval. For this, video files are divided into a number of frames or segments. After the segmentation process, images are trained for retrieval process, and from these, unwanted images are removed from the data set. The noise or unwanted image removal pseudo-code is shown below. In the code image, pixel value represents the value of the difference between the two adjacent image pixel values. By assuming a threshold for the image value, the duplicate images are found. After finding the duplicate image, it is removed from the data set. Clustering is used in many applications as a stand-alone tool to get insight into data distribution and as a pre-processing step for other algorithms (Ester et al., 1996). Specifically, it is used in pattern recognition, spatial data analysis, image processing, economic science document classification, etc. Hierarchical clustering algorithms are classified as agglomerative or divisive. BRICH uses clustering attribute (CA) and clustering feature hierarchy (CA_Hierarchy) for the formation of clusters. It perform multidimensional data objects. Every BRICH algorithm based on the memory-oriented information, that is, memory constrains, is involved in the processing of the data sets. This information is represented in Figures 6-10. For forming clusters, they use the amount of object in the cluster (A), the sum of all points in the data set (S) and need the square value of the all objects (P).

The proposed technique brings an effective result for cluster formation.

BRICH uses a novel approach to model the degree of inter-connectivity and closeness between each pair of clusters that takes into account the internal characteristics of the clusters themselves.

The digitalization of archival management has rapidly developed with the maturation of digital technology. With data's exponential growth, archival resources have transitioned from single modalities, such as text, images, audio and video, to integrated multimodal forms. This paper identifies key trends, gaps and areas of focus in the field. Furthermore, it proposes a theoretical organizational framework based on deep learning to address the challenges of managing archives in the era of big data.

Via a comprehensive systematic literature review, the authors investigate the field of multimodal archive resource organization and the application of deep learning techniques in archive organization. A systematic search and filtering process is conducted to identify relevant articles, which are then summarized, discussed and analyzed to provide a comprehensive understanding of existing literature.

The authors' findings reveal that most research on multimodal archive resources predominantly focuses on aspects related to storage, management and retrieval. Furthermore, the utilization of deep learning techniques in image archive retrieval is increasing, highlighting their potential for enhancing image archive organization practices; however, practical research and implementation remain scarce. The review also underscores gaps in the literature, emphasizing the need for more practical case studies and the application of theoretical concepts in real-world scenarios. In response to these insights, the authors' study proposes an innovative deep learning-based organizational framework. This proposed framework is designed to navigate the complexities inherent in managing multimodal archive resources, representing a significant stride toward more efficient and effective archival practices.

This study comprehensively reviews the existing literature on multimodal archive resources organization. Additionally, a theoretical organizational framework based on deep learning is proposed, offering a novel perspective and solution for further advancements in the field. These insights contribute theoretically and practically, providing valuable knowledge for researchers, practitioners and archivists involved in organizing multimodal archive resources.

The purpose of this paper is to report on a user-centred analysis of video digital libraries and to present users’ criteria based on concepts emerging directly from the responses of study participants. As a time-based and multi-channeled format, video warrants considerations for information delivery through interactive tools such as digital libraries.

A survey method was used to collect open-ended responses from participants. Content analysis was performed on the responses, and categories then emerged to form the coding scheme where simple and weighted frequencies were calculated to obtain a ranked set of users’ criteria. Cohen’s κ was 0.87, indicative of high-level of inter-coder reliability. In the end, 81 participants contributed a total of 385 open-ended responses, which were all then analysed and coded.

The emergent coding method and continuous refinements to the coding scheme ultimately produced 28 criteria (subcategories) under four primary categories. Criteria corresponding to “retrieval functionality” of video digital libraries emerged as the highest, or most frequently referenced, primary category, while the “user interface”, “collection qualities”, and “user support” followed, respectively.

The primary research contribution is a baseline for video digital libraries that can be applicable throughout design and evaluation. Future studies can utilise findings presented here as guidance for the initial design stages and/or for assessing systems via targeted evaluations.

While users’ criteria of digital libraries have been analysed from non-visual contexts, they have not been directly assessed as they pertain to users’ experiences and perceptions with video, which is needed as the nature and structure of video can influence users and use.

The purpose of this paper is to understand how typical users of YouTube judge the relevance of videos in leisure contexts; what are the reasons users give when judging video material as relevant or not relevant?

A naturalistic diary was performed in which 30 participants completed diaries providing details on their video relevance criteria. The analysis revealed 28 relevance criteria grouped into eight categories.

In total, 28 relevance criteria were identified through the analyses of the diaries’ content and they were grouped into eight categories. The findings revealed that criteria related to the content of the video are the most dominant group of criteria with topicality being the most dominant criterion. There is a considerable overlap between leisure relevance criteria and previous relevance criteria studies, but the importance of these criteria varies among different contexts. New criteria, e.g. habit emerged from the data which tend to be more related to leisure contexts.

The decision to follow a naturalistic approach reduced the level of control on the study. A further limitation can be found in the participants’ sample used in this study, all the participants of the main study were university or college students.

This study attempted to enrich the current literature by investigating users’ video relevance criteria in leisure contexts. This investigation might have implications on the design of video search systems.

Previous relevance criteria studies focussed on work contexts and the information judged was mainly in text format. This paper outlines new insights by investigating video relevance criteria in leisure context.

Multimedia retrieval is a complex and to some extent still unexplored area. Based on a full year of e‐mail requests addressed to a large film archive this study analyses what types of information needs real users have and how these needs are expressed. The findings include that the requesters make use of a broad range of need attributes in specifying their information needs. These attributes relate to the production, content, subject, context and screening of films. However, a few attributes – especially title, production year and director – account for the majority of the attribute instances. Further, as much as 43 per cent of the requests contain no information about the context that gives rise to the request. The current indexing of the archived material is restricted to production‐related attributes, and access to the material is, thus, frequently dependent on the archivists’ extensive knowledge of the archived material and films in general.