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Knowledge graphs (KGs) have become vitally important in modern recommender systems, effectively improving performance and interpretability. Fundamentally, recommender systems aim to identify user interests based on historical interactions…

Information Retrieval · Computer Science 2024-03-20 Zezhong Xu , Yincen Qu , Wen Zhang , Lei Liang , Huajun Chen

We introduce an approach to discovery informatics that uses so called knowledge graphs as the essential representation structure. Knowledge graph is an umbrella term that subsumes various approaches to tractable representation of large…

Artificial Intelligence · Computer Science 2015-04-29 Vit Novacek

Designing and implementing comprehensive IT-based support environments for KM in organizations is fraught with many problems. Solving them requires intimate knowledge about the information usage in knowledge works and the scopes of…

Digital Libraries · Computer Science 2011-12-23 Arijit Laha

Conversational agents are increasingly deployed in knowledge-intensive settings, where correct behavior depends on retrieving and applying domain-specific knowledge from large, proprietary, and unstructured corpora during live interactions…

Artificial Intelligence · Computer Science 2026-03-05 Quan Shi , Alexandra Zytek , Pedram Razavi , Karthik Narasimhan , Victor Barres

Quantum computing promises substantial speedups by exploiting quantum mechanical phenomena such as superposition and entanglement. Corresponding design methods require efficient means of representation and manipulation of quantum…

Quantum Physics · Physics 2023-11-15 Alwin Zulehner , Stefan Hillmich , Robert Wille

Deploying large language models (LLMs) to real scenarios for domain-specific question answering (QA) is a key thrust for LLM applications, which poses numerous challenges, especially in ensuring that responses are both accommodating to user…

Computation and Language · Computer Science 2024-06-11 Yichi Zhang , Zhuo Chen , Yin Fang , Yanxi Lu , Fangming Li , Wen Zhang , Huajun Chen

Answering temporal CQs over temporalized Description Logic knowledge bases (TKB) is a main technique to realize ontology-based situation recognition. In case the collected data in such a knowledge base is inaccurate, important query answers…

Logic in Computer Science · Computer Science 2023-07-31 Oliver Fernandez-Gil , Fabio Patrizi , Giuseppe Perelli , Anni-Yasmin Turhan

Knowledge conflicts commonly arise across diverse sources, and their prevalence has increased with the advent of LLMs. When dealing with conflicts between multiple contexts, also known as \emph{inter-context knowledge conflicts}, LLMs are…

Artificial Intelligence · Computer Science 2025-08-06 Xianda Zheng , Zijian Huang , Meng-Fen Chiang , Michael J. Witbrock , Kaiqi Zhao

We present efficient differentiable implementations of second-order multi-hop reasoning using a large symbolic knowledge base (KB). We introduce a new operation which can be used to compositionally construct second-order multi-hop templates…

Machine Learning · Computer Science 2019-05-28 William W. Cohen , Haitian Sun , R. Alex Hofer , Matthew Siegler

Experience-based planning domains (EBPDs) have been recently proposed to improve problem solving by learning from experience. EBPDs provide important concepts for long-term learning and planning in robotics. They rely on acquiring and using…

Artificial Intelligence · Computer Science 2019-03-06 Vahid Mokhtari , Luis Seabra Lopes , Armando Pinho , Roman Manevich

Description logic Knowledge and Action Bases (KAB) are a mechanism for providing both a semantically rich representation of the information on the domain of interest in terms of a description logic knowledge base and actions to change such…

Artificial Intelligence · Computer Science 2014-02-05 Babak Bagheri Hariri , Diego Calvanese , Marco Montali , Giuseppe De Giacomo , Riccardo De Masellis , Paolo Felli

In recent years, Knowledge Graph (KG) development has attracted significant researches considering the applications in web search, relation prediction, natural language processing, information retrieval, question answering to name a few.…

Information Retrieval · Computer Science 2022-05-19 Satvik Garg , Dwaipayan Roy

The notion of class is ubiquitous in computer science and is central in many formalisms for the representation of structured knowledge used both in knowledge representation and in databases. In this paper we study the basic issues…

Artificial Intelligence · Computer Science 2011-05-30 D. Calvanese , M. Lenzerini , D. Nardi

The semantic linked data model is at the core of the Web due to its ability to model real world entities, connect them via relationships and provide context, which could help to transform data into information and information into…

Human-Computer Interaction · Computer Science 2021-03-12 Anelia Kurteva , Hélène De Ribaupierre

Cyber-Physical Systems in general, and Intelligent Transport Systems (ITS) in particular use heterogeneous data sources combined with problem solving expertise in order to make critical decisions that may lead to some form of actions e.g.,…

Large language models (LLMs) often struggle with knowledge-intensive tasks due to a lack of background knowledge and a tendency to hallucinate. To address these limitations, integrating knowledge graphs (KGs) with LLMs has been intensively…

Computation and Language · Computer Science 2025-06-13 Yilin Xiao , Chuang Zhou , Qinggang Zhang , Bo Li , Qing Li , Xiao Huang

The paper discusses the basic principles and the architecture of the software toolkit for constructing knowledge-based systems which can be used cooperatively over computer networks and also embedded into larger software systems in…

Artificial Intelligence · Computer Science 2007-05-23 Dmitri Soshnikov

Real-world semantic or knowledge-based systems, e.g., in the biomedical domain, can become large and complex. Tool support for the localization and repair of faults within knowledge bases of such systems can therefore be essential for their…

Artificial Intelligence · Computer Science 2022-08-08 Patrick Rodler , Dietmar Jannach , Konstantin Schekotihin , Philipp Fleiss

This paper outlines a methodology for analyzing the representational support for knowledge-based decision-modeling in a broad domain. A relevant set of inference patterns and knowledge types are identified. By comparing the analysis results…

Artificial Intelligence · Computer Science 2013-03-26 Tze-Yun Leong

Multimodal search-based dialogue is a challenging new task: It extends visually grounded question answering systems into multi-turn conversations with access to an external database. We address this new challenge by learning a neural…

Computation and Language · Computer Science 2018-11-22 Shubham Agarwal , Ondrej Dusek , Ioannis Konstas , Verena Rieser