PDF Ebook about: Disambiguation
Disambiguation
List of ebooks and manuals about Disambiguation
24 documents available in our comprehensive collection of Disambiguation resources. Find practical guides, tutorials, and documentation to enhance your knowledge.
Word Sense Disambiguation (W05-0605.pdf)
159 KBEN 7 pages
A weakly supervised learning approach to word sense disambiguation (WSD) is presented, based on learning a word-independent context pair classification model,
now famous paper (acl2001.pdf)
49 KBEN 8 pages
Michele Banko and Eric Brill of Microsoft Research evaluated the performance of different learning methods on a natural language disambiguation task, confusion
Ant Colony WSD (C12-1146.pdf)
222 KBEN 16 pages
Ant Colony Algorithm outperforms Genetic and Simulated Annealing Algorithms in unsupervised word sense disambiguation, yielding better results and faster
NEDard: Using Multi-Sense Embeddings for Named Entity Disambiguation (Bachelor_Felix_Jablonski_2019.pdf)
1.01 MBEN 53 pages
This thesis deals with Named Entity Disambiguation, linking mentions of entities in a text to their unique entity in a knowledge base, such as Wikidata
Scaling to Very Very Large Corpora for Natural Language Disambiguation (P01-1005.pdf)
47 KBEN 8 pages
Michele Banko and Eric Brill of Microsoft Research evaluated the performance of different learning methods on a natural language disambiguation task, confusion
Massive-Scale Named Entity Disambiguation with Deep Learning and Data Augmentation (conll2018.pdf)
360 KBEN 10 pages
It proposes data augmentation and transfer learning to address scarce training data, demonstrating that bag-of-word embeddings outperform LSTMs in low-data scenarios, while LSTMs excel with larger datasets.
Word Sense Induction (E17-1009.pdf)
453 KBEN 13 pages
Researchers present an interpretable unsupervised knowledge-free word sense induction and disambiguation method, which matches state-of-the-art models in
A Survey of Data Provenance Techniques (TR618.pdf)
358 KBEN 25 pages
Data provenance is metadata describing the derivation history of a data product, essential for disambiguating data and enabling reuse.
BabelNet API (P12-3012.pdf)
356 KBEN 6 pages
Researchers present a multilingual Word Sense Disambiguation (WSD) API using BabelNet, a wide-coverage lexical knowledge base, to provide easy-to-use tools for
WSD System (C12-3031.pdf)
1.02 MBEN 8 pages
Researchers developed an online system for Word Sense Disambiguation (WSD) that allows users to run multiple state-of-the-art algorithms with minimal overhead,
GlossBERT (D19-1355.pdf)
232 KBEN 6 pages
Researchers propose GlossBERT, a BERT-based model for Word Sense Disambiguation (WSD) that leverages gloss knowledge from WordNet, achieving new
FreeLing Semantic Services (gwn2010.pdf)
564 KBEN 7 pages
1 provides semantic services based on WordNet and UKB databases, including word sense disambiguation, and offers text processing and language
gwn2010.pdf (gwn2010.pdf)
564 KBEN 7 pages
FreeLing is an open-source multilingual language processing library providing text processing and language annotation facilities.
Contextual Word Similarity (C12-1066.pdf)
162 KBEN 16 pages
Researchers propose a new measure of semantic similarity between words in context, exploiting syntactic/semantic structure of surrounding context, and test it...
http://www.aclweb.org/anthology/W/W11/W11-3413.pdf (W11-3413.pdf)
719 KBEN 9 pages
Two algorithms are proposed to address this issue: a Hidden Markov Model (HMM) and an n-gram model.
Access to file (Poster-2017-593.pdf)
478 KBEN 1 page
CERN Document Server's publication life cycle consists of three stages:
Ingestion (data from multiple sources),
Enrichment (automatic extraction, review, and...
A large DataBase of hypernymy relations extracted from the Web (lrec2016.pdf)
254 KBEN 8 pages
Researchers extracted over 400 million hypernymy relations from the CommonCrawl web corpus, creating a large database to support various Natural Language...
Construction of EPEC: A Reference Corpus for Basque Natural Language Processing (CLAW2006.pdf)
310 KBEN 14 pages
The construction of EPEC, a Basque language corpus, involves manual tagging at various levels (morphology, syntax) and aims to establish a reference for automatic processing through dependency structure analysis. This standard written Basque corpus is currently being enhanced...
pdf (2022.lrec-1.300.pdf)
857 KBEN 8 pages
Researchers are creating a WordNet for Latvian, based on the principles of the Princeton WordNet, using corpus evidence and the existing Tezaurs.lv online...
![Preview of [OpenAccess]](/images/pdf/9d/82/37/9d8237d4-2090-4d82-be66-a44789719260.png)
[OpenAccess] (82180337-semantic-rule-filtering-for-web-scale-relation-extraction.pdf)
238 KBEN 16 pages
Researchers propose a method to improve precision in web-scale relation extraction by utilizing a lexical semantic network, BabelNet, for semantic rule...
pdf (2023.eacl-main.59.pdf)
362 KBEN 16 pages
Researchers investigated whether pretrained contextual language models can distinguish between Hebrew homograph analyses, which is a challenging task due to...
pdf (W93-0307.pdf)
546 KBEN 7 pages
Lexical co-occurrence statistics are used in syntactic analysis of text, but suffer from sparsity of data.
Wikipedia Taxonomy Mapping (IJCAI09-343.pdf)
489 KBEN 6 pages
Ponzetto and Navigli propose a method to disambiguate Wikipedia categories using WordNet synsets, restructuring the resulting taxonomy. They demonstrate high accuracy in evaluation and enrich WordNet with Wikipedia instances.
Is Language Logical? A Study of Disjunction Scope Parameters (ELM1_paper_56.pdf)
306 KBEN 2 pages
Natural language, such as English and French, follows formal logic rules. The meaning of "I don't like apples or pears" corresponds to "I dislike both apples and pears" due to De Morgan's Law. This supports the idea that natural language coordinating conjunctions correspond to...
Popular Keywords
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To find more books about disambiguation, you can use related keywords: Pa Disambiguation , arabic word sense disambiguation 2010, disambiguation, Word Sense Disambiguation, Scaling to Very Very Large Corpora for Natural Language Disambiguation, NEDard: Using Multi-Sense Embeddings for Named Entity Disambiguation, Massive-Scale Named Entity Disambiguation with Deep Learning and Data Augmentation, Massive Scale Named Entity Disambiguation With Deep Learning And Data Augmentation
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