[PDF] Top 20 Parser Adaptation to the Biomedical Domain without Re Training
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Parser Adaptation to the Biomedical Domain without Re Training
... each parser the worst performing models tend to be those based on bag-of-words contexts (BOW, SG- news and ...on biomedical data (SG-bio) fared worse than the original (SG-news), due probably in large part ... See full document
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Unsupervised Linguistically Driven Reliable Dependency Parses Detection and Self Training for Adaptation to the Biomedical Domain
... against domain corpora outside of the data from which they were ...the biomedical domain where, due to the rapidly expanding body of biomedical literature, the need for increasingly ... See full document
9
Reranking and Self Training for Parser Adaptation
... broad-coverage parser which is rel- atively insensitive to textual ...gle domain using training data from that domain — the Wall Street Journal ( WSJ ) section of the Penn Treebank (Marcus et ... See full document
8
Self Training without Reranking for Parser Domain Adaptation and Its Impact on Semantic Role Labeling
... self- training in contribution to the SRL ...the training data and the use of the reranker, which may provide improvements in parse quality that are of a different kind of those most needed by the SRL ... See full document
8
Dependency Parser Adaptation with Subtrees from Auto Parsed Target Domain Data
... labeled training data and the test data come from the same domain; the subtree- based features collected from auto-parsed data are added to all the labeled training data to retrain the parsing ... See full document
6
Domain Adaptation of a Dependency Parser with a Class Class Selectional Preference Model
... new domain, many of the errors are related to wrong attachment of out-of-vocabulary ...target domain words, we attack this problem using a model of selectional preferences based on domain- specific ... See full document
6
Combining Active Learning and Partial Annotation for Domain Adaptation of a Japanese Dependency Parser
... dependency parser to new domains, and showed that active learning is not limited to single-domain ...in- domain training data needed for domain adapta- tion by up to ... See full document
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Reinforced Training Data Selection for Domain Adaptation
... The Predictor The Bi-LSTM parser proposed by Kiperwasser and Goldberg (2016) is the predictor. Baselines For dependency parsing, we use the same baselines introduced in the POS tagging task. Results The ... See full document
12
Robust Biomedical Event Extraction with Dual Decomposition and Minimal Domain Adaptation
... The Infectious Diseases track differs from the Genia track in two important ways. First, it introduces the event type Process that is allowed to have no ar- guments at all. Second, it comes with significantly less ... See full document
5
Automatic Generation of High Quality CCGbanks for Parser Domain Adaptation
... CCG Parser In each of the fol- lowing domain adaptation experiments, newly ob- tained CCGbanks are used to fine-tune the param- eters of the baseline parser described above, by ... See full document
11
Dependency Parsing and Domain Adaptation with LR Models and Parser Ensembles
... both training (for exam- ple, the SVM parsers we used required significant- ly longer to train than the MaxEnt parsers) and run-time (parsing with MBL models can be several times slower than with MaxEnt, or even ... See full document
7
A Word Clustering Approach to Domain Adaptation: Effective Parsing of Biomedical Texts
... in training and test data; (ii) learn a grammar from the word-clustered sentences in the training set; (iii) parse the word-clustered sen- tences in the test set; (iv) reintroduce the original tokens into ... See full document
6
Biomedical Relation Classification by single and multiple source domain adaptation
... same domain can contribute to performance enhancement justifying the perfor- mance gains in MSST ...adversarial training which might be attributed to joint learning better representation from shared and ... See full document
6
Pro3Gres Parser in the CoNLL Domain Adaptation Shared Task
... Multi-word terms, adjective-preposition construc- tions and frequent PP-arguments have strong collo- cational force. We have thus used the collocation extraction tool XTRACT (Smadja, 2003) to discover collocations from ... See full document
5
Self Training for Enhancement and Domain Adaptation of Statistical Parsers Trained on Small Datasets
... when training and test data are taken from different ...self- training in order to improve the quality of a parser and to adapt it to a different do- main, using only small amounts of manually ... See full document
8
Neural Domain Adaptation for Biomedical Question Answering
... Supervised Domain Adaptation In contrast to the unsupervised case, supervised domain adapta- tion assumes access to a small amount of labeled training data in the target ...supervised ... See full document
9
Domain Adaptation for Dependency Parsing via Self Training
... for domain adaptation of a dependency parser via ...ployed parser to measure the confidence into a parse ...chemical domain and by ... See full document
10
Multitask Parsing Across Semantic Representations
... Figure 3: Graphs from Figure 1, after conversion to the uni- fied DAG format (with pre-terminals omitted: each terminal drawn in place of its parent). Figure 3a presents a converted UCCA graph. Linkage nodes and edges ... See full document
13
Adapting the RASP System for the CoNLL07 Domain Adaptation Task
... this mapping are discussed in section 4. Given this mapping, we determined the subset of sentences in the (PTB) training data for which there was a sin- gle derivation in the grammar compatible with the set of ... See full document
5
Entropy based Training Data Selection for Domain Adaptation
... Training data selection is a common approach to domain adaptation. The challenge is to find a good measure for calculating the similarity between training sentences and the test data to ... See full document
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