Related papers: Open Annotations on Multimedia Web Resources

Linked Data (LD) as a web--based technology enables in principle the seamless, machine--supported integration, interplay and augmentation of all kinds of knowledge, into what has been labeled a huge knowledge graph. Despite decades of web…

Multimedia engages an audience through a combination of text, audio, still images, animation, video, or interactivity-based content formats. Along this vein, free platforms have been seen to allow budding enthusiasts to create multimedia…

Recommender Systems have proliferated as general-purpose approaches to model a wide variety of consumer interaction data. Specific instances make use of signals ranging from user feedback, item relationships, geographic locality, social…

Web applications development involves managing a high diversity of files and resources like code, pages or style sheets, implemented in different languages. To deal with the automatic generation of custom-made configurations of web…

Annotations are a critical component of visualizations, helping viewers interpret the visual representation and highlighting critical data insights. Despite their significant role, we lack an understanding of how annotations can be…

Web annotation has been receiving increased attention recently with the organization of the Open Annotation Collaboration and new tools for open annotation, such as Hypothes.is. We investigate the prevalence of orphaned annotations, where…

Multimedia content is of predominance in the modern Web era. Investigating how users interact with multimodal items is a continuing concern within the rapid development of recommender systems. The majority of previous work focuses on…

Audio-visual learning seeks to enhance the computer's multi-modal perception leveraging the correlation between the auditory and visual modalities. Despite their many useful downstream tasks, such as video retrieval, AR/VR, and…

The OpenCitations organization is working on ingesting citation data and bibliographic metadata directly provided by the community (e.g., scholars and publishers). The aim is to improve the general coverage of open citations, which is still…

With the rapid adoption of multimodal large language models (MLLMs) across diverse applications, there is a pressing need for task-centered, high-quality training data. A key limitation of current training datasets is their reliance on…

Data annotation and synthesis generally refers to the labeling or generating of raw data with relevant information, which could be used for improving the efficacy of machine learning models. The process, however, is labor-intensive and…

Retrieve information resources made by the machine processing may refer to multiple sources. A personal web as part of information resources in the Internet requires a feature that can be understood by computer machines. Therefore, in this…

Collaborative tagging systems, such as Delicious, CiteULike, and others, allow users to annotate resources, e.g., Web pages or scientific papers, with descriptive labels called tags. The social annotations contributed by thousands of users,…

The annotation of image and video data of large datasets is a fundamental task in multimedia information retrieval and computer vision applications. In order to support the users during the image and video annotation process, several…

The openness and accessibility of the Web has contributed greatly to its worldwide adoption. Uniform Resource Identifiers (URIs) are used for resource identification on the Web. A resource on the Web can be described in many ways, which…

We present a free and open-source tool for creating web-based surveys that include text annotation tasks. Existing tools offer either text annotation or survey functionality but not both. Combining the two input types is particularly…

Data annotation is an essential step for constructing new datasets. However, the conventional approach of data annotation through crowdsourcing is both time-consuming and expensive. In addition, the complexity of this process increases when…

Many recommendation systems limit user inputs to text strings or behavior signals such as clicks and purchases, and system outputs to a list of products sorted by relevance. With the advent of generative AI, users have come to expect richer…

SMCalFlow is a large corpus of semantically detailed annotations of task-oriented natural dialogues. The annotations use a dataflow approach, in which the annotations are programs which represent user requests. Despite the availability,…

Machine learning (ML) and artificial intelligence (AI) systems rely heavily on human-annotated data for training and evaluation. A major challenge in this context is the occurrence of annotation errors, as their effects can degrade model…