[PDF] Top 20 Automatic Domain Adaptation for Parsing
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Automatic Domain Adaptation for Parsing
... source domain adaptation has been done for other tasks ...of domain adaptation classification ...source domain plus the “general” pseudodomain (for capturing domain independent ... See full document
9
Automatic Domain Adaptation for Word Sense Disambiguation Based on Comparison of Multiple Classifiers
... when parsing a document collection of hetero- geneous ...parser adaptation. They proposed a method of parsing a sentence that first predicts ac- curacies for various parsing models using a ... See full document
9
Automatic Generation of High Quality CCGbanks for Parser Domain Adaptation
... CCG parsing as well as ones occurred in the conversion to the constituency ...the parsing performance in de- tail, the first author manually annotated a subset of randomly sampled 100 sentences from the ... See full document
11
Domain Adaptation for Syntactic and Semantic Dependency Parsing Using Deep Belief Networks
... on domain adaptation for dependency parsing and SRL are directly related to our ...that domain adaptation is hard for de- pendency parsing based on results in the CoNLL 2007 ... See full document
12
A Word Clustering Approach to Domain Adaptation: Effective Parsing of Biomedical Texts
... We present a simple and effective way to perform out-of-domain statistical parsing by drastically reducing lexical data sparseness in a PCFG-LA architecture. We replace terminal symbols with unsupervised ... See full document
6
Combining Active Learning and Partial Annotation for Domain Adaptation of a Japanese Dependency Parser
... on surface forms and part-of-speech (POS) tags of words, and first-order features between pairs of head and dependent words. Higher-order features that refer to chains of two or more dependencies, like the ones used in ... See full document
9
Dependency Parsing and Domain Adaptation with LR Models and Parser Ensembles
... ensembles. The main difference between our pars- er and a traditional LR parser is that we do not use an LR table derived from an explicit grammar to determine shift/reduce actions. Instead, we use a classifier with ... See full document
7
Improved Parsing and POS Tagging Using Inter Sentence Consistency Constraints
... Data for Domain Adaptation We perform do- main adaptation experiments in English using the WSJ PennTreebank (Marcus et al., 1993) and the QuestionBank (QTB) (Judge et al., 2006). In the WSJ → QTB ... See full document
11
Automatic Adaptation of Annotations
... annotation adaptation strategy, Model 3, leads to classifiers with significantly higher accuracy and to process- ing speeds that are several times ...pendency parsing, automatic annotation ... See full document
30
Automatic Accuracy Prediction for AMR Parsing
... To sum up, our observations for the out-of- domain data stand in some contrast to what we observe for the in-domain data. However, this out- come can be plausibly explained: assuming that the ... See full document
12
Embedding Semantic Similarity in Tree Kernels for Domain Adaptation of Relation Extraction
... “US”, are terms indicating an employment rela- tion between a person and a location. Rather than only matching the surface string of words, lexi- cal similarity enables soft matches between similar words in convolution ... See full document
10
Faster Parsing by Supertagger Adaptation
... We have used Sections 02-21 of CCGbank (Hock- enmaier and Steedman, 2007), the CCG version of the Penn Treebank (Marcus et al., 1993), as train- ing data for the newspaper domain. Sections 00 and 23 were used for ... See full document
11
Automatic Determination of a Domain Adaptation Method for Word Sense Disambiguation Using Decision Tree Learning
... Domain adaptation (DA), which involves adapting a classifier developed from source to target data, has been studied intensively in recent years. However, when DA for word sense disambiguation (WSD) was ... See full document
9
Multilingual Dependency Parsing and Domain Adaptation using DeSR
... Our implementation of the perceptron algorithm uses sparse data structures (hash maps) so that it can handle efficiently even large feature spaces in a single model. For example the feature space for the 2nd-order model ... See full document
7
Frustratingly Hard Domain Adaptation for Dependency Parsing
... POS types, the loss (difference in source and tar- get error) was: verbs (2%), conjunctions (5%), dig- its (23%), prepositions (4%), adjectives (3%), de- terminers (4%) and nouns (9%). 2 Two POS types stand out: digits ... See full document
5
Automatic Domain Adaptation Outperforms Manual Domain Adaptation for Predicting Financial Outcomes
... are domain-specific and require domain-specific re- sources including ...tomatic adaptation works ...a domain and this in- creases the risk that a word is misjudged if only the generic meaning ... See full document
14
Towards Domain Adaptation for Parsing Web Data
... whether parsing could be improved by adding data to the small answer training set 1) from the domain that is easiest to parse: emails, 2) from the news domain because of its similar average sentence ... See full document
8
Semi supervised Domain Adaptation for Dependency Parsing
... multi-source domain adaptation problem assumes there are labeled datasets for multiple source ...target domain, the chal- lenge is how to effectively combine knowledge in the source ...constituent ... See full document
10
Domain Adaptation for Parsing
... performed domain adaptation for constituent parsing using two different ...target domain consists of spontaneous dialogues involv- ing collaboration between ...target domain sentences ... See full document
9
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