[LIBRO][B] Machine learning for text: An introduction
CC Aggarwal, CC Aggarwal - 2018 - Springer
The extraction of useful insights from text with various types of statistical algorithms is
referred to as text mining, text analytics, or machine learning from text. The choice of …
referred to as text mining, text analytics, or machine learning from text. The choice of …
Simlex-999: Evaluating semantic models with (genuine) similarity estimation
We present SimLex-999, a gold standard resource for evaluating distributional semantic
models that improves on existing resources in several important ways. First, in contrast to …
models that improves on existing resources in several important ways. First, in contrast to …
[LIBRO][B] Sentiment analysis and opinion mining
B Liu - 2022 - books.google.com
Sentiment analysis and opinion mining is the field of study that analyzes people's opinions,
sentiments, evaluations, attitudes, and emotions from written language. It is one of the most …
sentiments, evaluations, attitudes, and emotions from written language. It is one of the most …
[LIBRO][B] Sentiment analysis: Mining opinions, sentiments, and emotions
B Liu - 2020 - books.google.com
Sentiment analysis is the computational study of people's opinions, sentiments, emotions,
moods, and attitudes. This fascinating problem offers numerous research challenges, but …
moods, and attitudes. This fascinating problem offers numerous research challenges, but …
A survey of text summarization techniques
Numerous approaches for identifying important content for automatic text summarization
have been developed to date. Topic representation approaches first derive an intermediate …
have been developed to date. Topic representation approaches first derive an intermediate …
Automatic summarization
It has now been 50 years since the publication of Luhn's seminal paper on automatic
summarization. During these years the practical need for automatic summarization has …
summarization. During these years the practical need for automatic summarization has …
Lexrank: Graph-based lexical centrality as salience in text summarization
We introduce a stochastic graph-based method for computing relative importance of textual
units for Natural Language Processing. We test the technique on the problem of Text …
units for Natural Language Processing. We test the technique on the problem of Text …
A survey on clustering algorithms for wireless sensor networks
The past few years have witnessed increased interest in the potential use of wireless sensor
networks (WSNs) in applications such as disaster management, combat field …
networks (WSNs) in applications such as disaster management, combat field …
[PDF][PDF] Towards answering opinion questions: Separating facts from opinions and identifying the polarity of opinion sentences
H Yu, V Hatzivassiloglou - Proceedings of the 2003 conference on …, 2003 - aclanthology.org
Opinion question answering is a challenging task for natural language processing. In this
paper, we discuss a necessary component for an opinion question answering system …
paper, we discuss a necessary component for an opinion question answering system …
[LIBRO][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 …