Related papers: Token-Curated Registry with Citation Graph
Citation recommendation systems have attracted much academic interest, resulting in many studies and implementations. These systems help authors automatically generate proper citations by suggesting relevant references based on the text…
Automatic chord recognition (ACR) extracts time-aligned chord labels from music audio recordings. Despite recent advances, ACR still struggles with oversegmentation, data scarcity, and imbalance, especially in recognizing complex chords…
In code review, generating structured and relevant comments is crucial for identifying code issues and facilitating accurate code changes that ensure an efficient code review process. Well-crafted comments not only streamline the code…
Mining the hierarchical structure of Internet review topics and realizing a fine classification of review texts can help alleviate users' information overload. However, existing hierarchical topic classification methods primarily rely on…
Ranking models have achieved promising results, but it remains challenging to design personalized ranking systems to leverage user profiles and semantic representations between queries and documents. In this paper, we propose a topic-based…
Constructing taxonomies from citation graphs is essential for organizing scientific knowledge, facilitating literature reviews, and identifying emerging research trends. However, manual taxonomy construction is labor-intensive,…
Peer review is a laborious, yet essential, part of academic publishing with crucial impact on the scientific endeavor. The current lack of incentives and transparency harms the credibility of this process. Researchers are neither rewarded…
Cross-referencing, which links passages of text to other related passages, can be a valuable study aid for facilitating comprehension of a text. However, cross-referencing requires first, a comprehensive thematic knowledge of the entire…
The paper provides statistical theory and intuition for personalized PageRank (called "PPR"): a popular technique that samples a small community from a massive network. We study a setting where the entire network is expensive to obtain…
Knowledge graph is generally incorporated into recommender systems to improve overall performance. Due to the generalization and scale of the knowledge graph, most knowledge relationships are not helpful for a target user-item prediction.…
In all domains and sectors, the demand for intelligent systems to support the processing and generation of digital content is rapidly increasing. The availability of vast amounts of content and the pressure to publish new content quickly…
Generative diffusion models have emerged as powerful tools to synthetically produce training data, offering potential solutions to data scarcity and reducing labelling costs for downstream supervised deep learning applications. However,…
Crowdsourcing systems have been used to accumulate massive amounts of labeled data for applications such as computer vision and natural language processing. However, because crowdsourced labeling is inherently dynamic and uncertain,…
The purpose of the paper is to propose models to reduce the semantic complexity in heterogeneous DLs. The aim is to introduce value-added services (treatment of term vagueness and document re-ranking) that gain a certain quality in DLs if…
Recent advancements in Deep Learning-based Handwritten Text Recognition (HTR) have led to models with remarkable performance on both modern and historical manuscripts in large benchmark datasets. Nonetheless, those models struggle to obtain…
Modern Code Review (MCR) is an informal tool-assisted quality assurance practice. It relies on the asynchronous communication among the authors of code changes and reviewers, who are developers that provide feedback. However, from candidate…
Although considerable efforts have been devoted to transformer-based ranking models for document search, the relevance-efficiency tradeoff remains a critical problem for ad-hoc ranking. To overcome this challenge, this paper presents BECR…
Modern Code Review (MCR) is a widely known practice of software quality assurance. However, the existing body of knowledge of MCR is currently not understood as a whole. Objective: Our goal is to identify the state of the art on MCR,…
The field of scientometrics has shown the power of citation-based clusters for literature analysis, yet this technique has barely been used for information retrieval tasks. This work evaluates the performance of citation based-clusters for…
Large text corpora, such as Reddit posts, have become an increasingly prevalent site of qualitative inquiry. However, most large text corpora are intractable for qualitative researchers. Instead, teams rely on statistical subsampling to…