Related papers: TT-RecS: The Taxonomic Trace Recommender System
Successful development of software systems involves efficient navigation among software artifacts. One state-of-practice approach to structure information is to establish trace links between artifacts, a practice that is also enforced by…
Language-integrated provenance builds on language-integrated query techniques to make provenance information explaining query results readily available to programmers. In previous work we have explored language-integrated approaches to…
In open source software development, the reuse of existing artifacts has been widely adopted to avoid redundant implementation work. Reusable artifacts are considered more efficient and reliable than developing software components from…
We propose a new technique to infer the structure and extract the tokens of data from the semi-structured web sources which are generated using a consistent template or layout with some implicit regularities. The attributes are extracted…
Taking advantage of a recently discovered associativity property of rule compositions, we extend the classical concurrency theory for rewriting systems over adhesive categories. We introduce the notion of tracelets, which are defined as…
Although computer science papers are often accompanied by software artifacts, connecting research papers to their software artifacts and vice versa is not always trivial. First of all, there is a lack of well-accepted standards for how such…
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…
Background: Traceability between software artifacts enhances the value of the information those artifacts contain, but only when the links themselves are reliable. Link quality is known to depend on explicit factors such as the traced…
Recent breakthroughs in deep-learning (DL) approaches have resulted in the dynamic generation of trace links that are far more accurate than was previously possible. However, DL-generated links lack clear explanations, and therefore…
With the development of the online education system, personalized education recommendation has played an essential role. In this paper, we focus on developing path recommendation systems that aim to generating and recommending an entire…
Citation analysis, as a tool for quantitative studies of science, has long emphasized direct citation relations, leaving indirect or high order citations overlooked. However, a series of early and recent studies demonstrate the existence of…
Recommender systems assist users in navigating complex information spaces and focus their attention on the content most relevant to their needs. Often these systems rely on user activity or descriptions of the content. Social annotation…
Recommender systems (RSs) aim to help users to effectively retrieve items of their interests from a large catalogue. For a quite long period of time, researchers and practitioners have been focusing on developing accurate RSs. Recent years…
The rapid evolution of large language models (LLMs) represents a substantial leap forward in natural language understanding and generation. However, alongside these advancements come significant challenges related to the accountability and…
A prerequisite is anything that you need to know or understand first before attempting to learn or understand something new. In the current work, we present a method of finding prerequisite relations between concepts using related…
In order to design and implement tracers, one must decide what exactly to trace and how to produce this trace. On the one hand, trace designs are too often guided by implementation concerns and are not as useful as they should be. On the…
As a fundamental task in computational chemistry, retrosynthesis prediction aims to identify a set of reactants to synthesize a target molecule. Existing template-free approaches only consider the graph structures of the target molecule,…
With the increasing need of personalised decision making, such as personalised medicine and online recommendations, a growing attention has been paid to the discovery of the context and heterogeneity of causal relationships. Most existing…
Modeling the complex interactions between users and items as well as amongst items themselves is at the core of designing successful recommender systems. One classical setting is predicting users' personalized sequential behavior (or…
A reciprocal recommendation problem is one where the goal of learning is not just to predict a user's preference towards a passive item (e.g., a book), but to recommend the targeted user on one side another user from the other side such…