[PDF] Top 20 Instance Weighting for Domain Adaptation in NLP
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Instance Weighting for Domain Adaptation in NLP
... From the table, we can see that in most exper- iments, removing these predicted “misleading” ex- amples improved the performance over the baseline. In some experiments (Oncology, CTS, u00, u01), the largest improvement ... See full document
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Instance Weighting for Neural Machine Translation Domain Adaptation
... Instance weighting has been widely applied to phrase-based machine translation domain ...two instance weighting technologies, i.e., sentence weighting and domain ... See full document
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Discriminative Instance Weighting for Domain Adaptation in Statistical Machine Translation
... for instance-weighting phrase pairs in an out-of-domain corpus in order to improve in-domain ...and instance-feature weights are learned at the same time using an efficient ... See full document
9
Better Fine-Tuning via Instance Weighting for Text Classification
... Text classification is one of the fundamental tasks in Nat- ural Language Processing (NLP) with many important ap- plications such as sentiment analysis (Landeiro and Cu- lotta, 2016; Xu et al., 2017; Zhang, ... See full document
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Not All Dialogues are Created Equal: Instance Weighting for Neural Conversational Models
... an instance weighting approach to address some of these ...on domain adaptation for neural response gener- ation, using a combination of online and offline human ... See full document
11
Sentence Level Instance Weighting for Graph Based and Transition Based Dependency Parsing
... one domain in a model induced from data in an- other domain, or they have promoted frequent tar- get domain classes if they were less frequent in the source ...using instance weight- ing, but ... See full document
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Embedding Semantic Similarity in Tree Kernels for Domain Adaptation of Relation Extraction
... We proposed syntactic tree kernels enriched by lexical semantic similarity to tackle the portabil- ity of a relation extractor to different domains. The results of diverse kernels exploiting (i) Brown clustering and (ii) ... See full document
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Frustratingly Easy Domain Adaptation
... of domain adaptation is to develop learn- ing algorithms that can be easily ported from one domain to another—say, from newswire to biomed- ical ...in NLP because we are often in the situation ... See full document
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Segmentation for Domain Adaptation in Arabic
... 4.1 Challenges of Dialectal Data Collection There are over 22 Arab countries with 22 national dialects and even larger number of sub-dialects. The population ranges from around 100m to less than 1m. Natural Language ... See full document
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Automatic Domain Adaptation Outperforms Manual Domain Adaptation for Predicting Financial Outcomes
... Many NLP applications 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 ... See full document
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A Hassle Free Unsupervised Domain Adaptation Method Using Instance Similarity Features
... unsupervised domain adaptation is to “couple” the learning of weights for target-specific features with that of common ...for NLP tasks, the actual space where input vectors lie can have a lower ... See full document
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Importance weighting and unsupervised domain adaptation of POS taggers: a negative result
... Many NLP tasks rely on the availability of anno- tated data. The majority of annotated data, how- ever, is sampled from newswire corpora. The performance of NLP systems, e.g., part-of-speech (POS) tagger, ... See full document
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Data point selection for cross language adaptation of dependency parsers
... of instance weighting, similar to what is often used for correcting sample selection bias or for domain adaptation, to improve the approach in Ze- man and Resnik (2008) by selecting only ... See full document
5
Domain Adaptation with Active Learning for Coreference Resolution
... an NLP task in a spe- cific domain, one needs to collect a text corpus in the domain and annotate it to serve as training ...other NLP tasks, ... See full document
9
Query Weighting for Ranking Model Adaptation
... source domain to the target domain where no rank labels of doc- uments are available, which is referred to as query ...Query weighting is a key step in ranking model ...importance weighting at ... See full document
11
Active Sentiment Domain Adaptation
... Domain adaptation is an important techno- logy to handle domain dependence pro- blem in sentiment analysis ...sentiment domain adaptation ap- proach to handle this ...source ... See full document
11
Feature-Level Domain Adaptation
... ”global” domain shifts such as translations or rotations in the feature space, but they are less effective when the domain shift is ”local” in the sense that it strongly ... See full document
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Sentiment Domain Adaptation with Multiple Sources
... SCL, domain adap- tation based on structural correspondence learn- ing (Blitzer et ...SFA, domain adap- tation based on spectral feature alignment (Pan et ...source domain sce- nario by first ... See full document
10
Instance Based Generation for Interactive Restricted Domain Question Answering Systems
... the domain of the system is ...the domain restrictions as given by the application, can interactively request more information from the user until the users’ intent has been ... See full document
12
Domain Ontology Learning Enhanced by Optimized Relation Instance in DBpedia
... recognized as “pseudo” hyponymy by relation knowledge base, no matter if these pairs are inserted in the enrich- ment step or exist in the original Wikipedia taxonomy or article tags. True hyponymy relations are other ... See full document
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