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The multi-document summarization task requires the designed summarizer to generate a short text that covers the important information of original documents and satisfies content diversity. This paper proposes a multi-document summarization…

Computation and Language · Computer Science 2023-03-07 Bing Ma

Tables are a primary medium for conveying critical information in administrative domains, yet their complexity hinders utilization by Large Language Models (LLMs). This paper introduces the Theme-Explanation Structure-based Table…

Computation and Language · Computer Science 2025-07-10 TaeYoon Kwack , Jisoo Kim , Ki Yong Jung , DongGeon Lee , Heesun Park

In this paper, we develop a neural summarization model which can effectively process multiple input documents and distill Transformer architecture with the ability to encode documents in a hierarchical manner. We represent cross-document…

Computation and Language · Computer Science 2019-05-31 Yang Liu , Mirella Lapata

In the Query Focused Multi-Document Summarization (QF-MDS) task, a set of documents and a query are given where the goal is to generate a summary from these documents based on the given query. However, one major challenge for this task is…

Computation and Language · Computer Science 2020-11-04 Md Tahmid Rahman Laskar , Enamul Hoque , Jimmy Xiangji Huang

Aspect-based summarization has attracted significant attention for its ability to generate more fine-grained and user-aligned summaries. While most existing approaches assume a set of predefined aspects as input, real-world scenarios often…

Computation and Language · Computer Science 2025-10-09 Yong-En Tian , Yu-Chien Tang , An-Zi Yen , Wen-Chih Peng

In online clustering problems, there is often a large amount of uncertainty over possible cluster assignments that cannot be resolved until more data are observed. This difficulty is compounded when clusters follow complex distributions, as…

Machine Learning · Statistics 2026-04-17 Connie Trojan , Pavel Myshkov , Paul Fearnhead , James Hensman , Tom Minka , Christopher Nemeth

Contextual Markov Decision Processes (CMDPs) offer a framework for sequential decision-making under external signals, but existing methods often fail to generalize in high-dimensional or unstructured contexts, resulting in excessive…

Artificial Intelligence · Computer Science 2025-10-06 Peidong Liu , Junjiang Lin , Shaowen Wang , Yao Xu , Haiqing Li , Xuhao Xie , Siyi Wu , Hao Li

In today's Web and social network environments, query workloads include ad hoc and OLAP queries, as well as iterative algorithms that analyze data relationships (e.g., link analysis, clustering, learning). Modern DBMSs support ad hoc and…

Databases · Computer Science 2012-08-02 Svilen R. Mihaylov , Zachary G. Ives , Sudipto Guha

Choosing a suitable deep learning architecture for multimodal data fusion is a challenging task, as it requires the effective integration and processing of diverse data types, each with distinct structures and characteristics. In this…

Machine Learning · Computer Science 2025-01-22 Abdelmadjid Chergui , Grigor Bezirganyan , Sana Sellami , Laure Berti-Équille , Sébastien Fournier

In this paper, we present the guidelines for an XML-based approach for the sociological study of Web data such as the analysis of mailing lists or databases available online. The use of an XML warehouse is a flexible solution for storing…

Supply Chain Management requires addressing a variety of complex decision-making challenges, from sourcing strategies to planning and execution. Over the last few decades, advances in computation and information technologies have enabled…

Artificial Intelligence · Computer Science 2025-07-30 David Simchi-Levi , Konstantina Mellou , Ishai Menache , Jeevan Pathuri

This paper presents a methodology for summarization from multiple documents which are about a specific topic. It is based on the specification and identification of the cross-document relations that occur among textual elements within those…

Computation and Language · Computer Science 2016-08-31 Stergos D. Afantenos , Irene Doura , Eleni Kapellou , Vangelis Karkaletsis

Selectivity estimation - the problem of estimating the result size of queries - is a fundamental problem in databases. Accurate estimation of query selectivity involving multiple correlated attributes is especially challenging. Poor…

Databases · Computer Science 2019-06-19 Shohedul Hasan , Saravanan Thirumuruganathan , Jees Augustine , Nick Koudas , Gautam Das

XML has emerged as the standard for representing and exchanging data on the World Wide Web. It is critical to have efficient mechanisms to store and query XML data to exploit the full power of this new technology. Several researchers have…

Databases · Computer Science 2010-10-11 Mustafa Atay , Yezhou Sun , Dapeng Liu , Shiyong Lu , Farshad Fotouhi

Today's database is associated with interoperability between different domains and applications. This consequently results in the importance of data portability in database. XML format fits the requirements and it has been increasingly used…

Databases · Computer Science 2010-10-07 Mikael Fernandus Simalango

Text summarization is a well-studied problem that deals with deriving insights from unstructured text consumed by humans, and it has found extensive business applications. However, many real-life tasks involve generating a series of actions…

Computation and Language · Computer Science 2024-07-19 Vishal Pallagani , Biplav Srivastava , Nitin Gupta

Database system architectures are undergoing revolutionary changes. Algorithms and data are being unified by integrating programming languages with the database system. This gives an extensible object-relational system where non-procedural…

Databases · Computer Science 2007-05-23 Jim Gray

The technology of automatic document summarization is maturing and may provide a solution to the information overload problem. Nowadays, document summarization plays an important role in information retrieval. With a large volume of…

Information Retrieval · Computer Science 2012-04-10 Mohsen Pourvali , Mohammad Saniee Abadeh

We provide methods for in-database support of decision making under uncertainty. Many important decision problems correspond to selecting a package (bag of tuples in a relational database) that jointly satisfy a set of constraints while…

Databases · Computer Science 2021-03-12 Matteo Brucato , Nishant Yadav , Azza Abouzied , Peter J. Haas , Alexandra Meliou

In keyword search, when user cannot get what she wants, query refinement is needed and reason can be various. We first give a thorough categorization of the reason, then focus on solving one category of query refinement problem in the…

Databases · Computer Science 2012-11-08 Yong Zeng , Zhifeng Bao , Guoliang Li , Tok Wang Ling , Jiaheng Lu
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