A brief survey of text mining: Classification, clustering and extraction techniques
The amount of text that is generated every day is increasing dramatically. This tremendous
volume of mostly unstructured text cannot be simply processed and perceived by computers …
volume of mostly unstructured text cannot be simply processed and perceived by computers …
More data, more relations, more context and more openness: A review and outlook for relation extraction
Relational facts are an important component of human knowledge, which are hidden in vast
amounts of text. In order to extract these facts from text, people have been working on …
amounts of text. In order to extract these facts from text, people have been working on …
Two are better than one: Joint entity and relation extraction with table-sequence encoders
Named entity recognition and relation extraction are two important fundamental problems.
Joint learning algorithms have been proposed to solve both tasks simultaneously, and many …
Joint learning algorithms have been proposed to solve both tasks simultaneously, and many …
[PDF][PDF] Lexicalized Dependency Paths Based Supervised Learning for Relation Extraction.
H Sun, R Grishman - Computer Systems Science & Engineering, 2022 - cdn.techscience.cn
Log-linear models and more recently neural network models used for supervised relation
extraction requires substantial amounts of training data and time, limiting the portability to …
extraction requires substantial amounts of training data and time, limiting the portability to …
[图书][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 …
Multilingual knowledge graph embeddings for cross-lingual knowledge alignment
Many recent works have demonstrated the benefits of knowledge graph embeddings in
completing monolingual knowledge graphs. Inasmuch as related knowledge bases are built …
completing monolingual knowledge graphs. Inasmuch as related knowledge bases are built …
[PDF][PDF] Relation extraction: Perspective from convolutional neural networks
TH Nguyen, R Grishman - Proceedings of the 1st workshop on …, 2015 - aclanthology.org
Up to now, relation extraction systems have made extensive use of features generated by
linguistic analysis modules. Errors in these features lead to errors of relation detection and …
linguistic analysis modules. Errors in these features lead to errors of relation detection and …
[PDF][PDF] Incremental joint extraction of entity mentions and relations
We present an incremental joint framework to simultaneously extract entity mentions and
relations using structured perceptron with efficient beam-search. A segment-based decoder …
relations using structured perceptron with efficient beam-search. A segment-based decoder …
N-ary relation extraction using graph state lstm
Cross-sentence $ n $-ary relation extraction detects relations among $ n $ entities across
multiple sentences. Typical methods formulate an input as a\textit {document graph} …
multiple sentences. Typical methods formulate an input as a\textit {document graph} …
[HTML][HTML] Open information extraction from the web
Open information extraction from the web Page 1 68 communications of the acm | december
2008 | vol. 51 | no. 12 review articles will build systems that fuse relevant pieces of …
2008 | vol. 51 | no. 12 review articles will build systems that fuse relevant pieces of …