Word sense disambiguation: A survey
R Navigli - ACM computing surveys (CSUR), 2009 - dl.acm.org
Word sense disambiguation (WSD) is the ability to identify the meaning of words in context
in a computational manner. WSD is considered an AI-complete problem, that is, a task …
in a computational manner. WSD is considered an AI-complete problem, that is, a task …
Natural language processing
KR Chowdhary, KR Chowdhary - Fundamentals of artificial intelligence, 2020 - Springer
The abundant volume of natural language text in the connected world, though having a
large content of knowledge, but it is becoming increasingly difficult to disseminate it by a …
large content of knowledge, but it is becoming increasingly difficult to disseminate it by a …
Automatic summarization
I Mani - 2001 - torrossa.com
When I planned this book in 1999, it was intended to be a survey of current work in text
summarization. The survey would discuss various efforts in the context of a framework for …
summarization. The survey would discuss various efforts in the context of a framework for …
[图书][B] Automatic text summarization
JM Torres-Moreno - 2014 - books.google.com
Textual information in the form of digital documents quickly accumulates to create huge
amounts of data. The majority of these documents are unstructured: it is unrestricted text and …
amounts of data. The majority of these documents are unstructured: it is unrestricted text and …
Textual keyword extraction and summarization: State-of-the-art
With the advent of Web 2.0, there exist many online platforms that results in massive textual
data production such as social networks, online blogs, magazines etc. This textual data …
data production such as social networks, online blogs, magazines etc. This textual data …
Text summarization using a trainable summarizer and latent semantic analysis
This paper proposes two approaches to address text summarization: modified corpus-based
approach (MCBA) and LSA-based TRM approach (LSA+ TRM). The first is a trainable …
approach (MCBA) and LSA-based TRM approach (LSA+ TRM). The first is a trainable …
Using lexical chains for keyword extraction
Keywords can be considered as condensed versions of documents and short forms of their
summaries. In this paper, the problem of automatic extraction of keywords from documents is …
summaries. In this paper, the problem of automatic extraction of keywords from documents is …
Efficiently computed lexical chains as an intermediate representation for automatic text summarization
HG Silber, KF McCoy - Computational Linguistics, 2002 - direct.mit.edu
While automatic text summarization is an area that has received a great deal of attention in
recent research, the problem of efficiency in this task has not been frequently addressed …
recent research, the problem of efficiency in this task has not been frequently addressed …
A comparative study of opinion summarization techniques
S Bhatia - IEEE Transactions on Computational Social Systems, 2020 - ieeexplore.ieee.org
In the Web 3.0 platforms, enormous amount of information is shared whereby individuals
express their thoughts and opinions and learn from others' experiences. Many e-commerce …
express their thoughts and opinions and learn from others' experiences. Many e-commerce …
Exploiting neighborhood knowledge for single document summarization and keyphrase extraction
Document summarization and keyphrase extraction are two related tasks in the IR and NLP
fields, and both of them aim at extracting condensed representations from a single text …
fields, and both of them aim at extracting condensed representations from a single text …