Live briefing
Everything about Multi-document summarization
Procedure extracting information from similar documents
Multi-document summarization is an automatic procedure aimed at extraction of information from multiple texts written about the same topic. The resulting summary report allows individual users, such as professional information consumers, to quickly familiarize themselves with information contained in a large cluster of documents. In such a way, multi-document summarization systems are complementing the news aggregators performing the next step down the road of coping with information overload. Wikipedia →
🧭 Start here: a 6-step reading path
- Read the overview: Multi-document summarizationA 5-minute orientation
- Skim a recent paper: Multi-document Summarization via Deep Learning Techniques: A SurveyInfluential work since 2022
- Pick up a classic book: Computational Linguistics and Intelligent Text ProcessingThe most-reprinted book on the subject
- Read the landmark paper: Extractive multi-document summarization using multilayer networksCited 58 times
- Go sideways: Automatic summarizationA closely related topic
- Go sideways: Dragomir R. RadevA closely related topic
📖 Definitions
No dictionary entry for this exact phrase.
🗂️ The subject at a glance
🏆 Landmark papers (most cited)
Extractive multi-document summarization using multilayer networks
MULTI‐DOCUMENT SUMMARIZATION OF EVALUATIVE TEXT
A document-sensitive graph model for multi-document summarization
Multi-document summarization using closed patterns
Multi-document summarization based on the Yago ontology
Improving Multi-Document Summarization via Text Classification
Weighted consensus multi-document summarization
Automatic Multi Document Summarization Approaches
🆕 Influential since 2022
Multi-document Summarization via Deep Learning Techniques: A Survey
Hybrid multi-document summarization using pre-trained language models
Multi-document extractive text summarization based on firefly algorithm
Decomposition–based multi-objective differential evolution for extractive multi-document automatic text summarization
Multi-document summarization for patent documents based on generative adversarial network
📚 Books worth reading
Computational Linguistics and Intelligent Text ProcessingAlexander Gelbukh · 2003
Natural Language Processing and Information SystemsElisabeth Métais · 2005
High Impact Resumes & LettersRonald L. Krannich, Ronald L Krannich · 1982
The Conspirators HierarchyJohn Coleman · 1992
Treaty Occupationay ToxicologySuelen Queiroz · 2010
Intelligent Information and Database SystemsAli Selamat · 2013
Advances in Computing, Communication, and ControlSrija Unnikrishnan · 2013- 📕Thirteenth International Work Shop on Research Issues in Data EngineeringIndia) International Workshop on Research Issues in Data Engineering (13th 2003 Hyderabad · 2003
Ranked by number of editions on Open Library, a rough measure of how lasting a book is.
🔗 Related topics
- Automatic summarization Automatic summarization is the process of shortening a set of data computationally, to create a subset (a summary) that represents the most important or…
- Dragomir R. Radev Dragomir R. Radev (August 7, 1968 – March 29, 2023) was an American computer scientist who was a professor at Yale University, working on natural language…
- Information retrieval In computing and information science, information retrieval (IR) is the task of identifying and retrieving information system resources that are relevant…
- Human–computer information retrieval Human–computer information retrieval (HCIR) is the study and engineering of information retrieval techniques that bring human intelligence into the search…
- Multimedia information retrieval Multimedia information retrieval (MMIR or MIR) is a research discipline of computer science that aims at extracting semantic information from multimedia…
- Information extraction Information extraction (IE) is the task of automatically extracting structured information from unstructured and/or semi-structured machine-readable documents…
- Knowledge extraction Knowledge extraction is the creation of knowledge from structured (relational databases, XML) and unstructured (text, documents, images) sources. The resulting…
- Cross-language information retrieval Cross-language information retrieval (CLIR) is a subfield of information retrieval dealing with retrieving information written in a language different…