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A Semi supervised Approach for Natural Language Call Routing
... A number of works have recently been published on natural language call classification. B. Car- penter, J. Chu-Carroll, C.-H. Lee and H.-K. Kuo proposed approaches using a vector-based in- formation ... See full document
5
Vector based Natural Language Call Routing
... Based on the statistical discriminating power of the n-gram terms extracted from the caller's request, the caller is 1 routed to the appropriate destination, 2 transferred to a human ope[r] ... See full document
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A Semi-supervised Approach for Generating a Table-of-Contents
... In this research, we use word clustering information to make the learning model take into account semantic information, in terms of the word similarity. With this information, we can choose better words which are ... See full document
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Using the Mutual k Nearest Neighbor Graphs for Semi supervised Classification on Natural Language Data
... We first evaluated the quality of the graphs apart from specific classification algorithms using the φ- edge ratio of graphs. Our experimental results show that the mutual k-NN graphs have a smaller num- ber of edges ... See full document
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Image Captioning with Very Scarce Supervised Data: Adversarial Semi Supervised Learning Approach
... a natural language description of a given im- ...a natural language, which exhibits free-form and manageable characteristics useful to applica- tions such as language based image or ... See full document
12
Dual Supervised Learning for Natural Language Understanding and Generation
... Natural language understanding (NLU) and natural language generation (NLG) are both critical research topics in the NLP and dia- logue ...fields. Natural language understanding ... See full document
6
Word Sense Disambiguation by Combining Labeled Data Expansion and Semi Supervised Learning Method
... Various methods have been proposed for WSD (Navigli, 2009). Unsupervised approaches such as clustering based methods (Pedersen, 2006) and ex- tended Lesk (Lesk, 1986) have been shown to do well (Baldwin et al., 2010), ... See full document
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Recognizing Explicit and Implicit Hate Speech Using a Weakly Supervised Two path Bootstrapping Approach
... The error of our model comes from semantic drift in bootstrapping learning, which partially results from the complexity and dynamics of language. Specifically, we found dynamic word sense of slurs and ... See full document
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A Semi Supervised Approach for Gender Identification
... State-of-the-art author profiling/gender identification pro- posals use mostly surface-oriented features: function words, most frequent words, triples and/or pairs of fre- quently co-occurring words, part of speech (POS) ... See full document
6
Three phase training to address data sparsity in Neural Machine Translation
... across language pairs, thereby pro- viding high quality translations de- spite the lack of large parallel cor- ...integrated approach which combines weakly supervised and semi- ... See full document
10
Cross Language Text Classification by Model Translation and Semi Supervised Learning
... Finally, also closely related is the work carried out in the field of sentiment and subjectivity analysis for cross-lingual classification of opinions. For in- stance, (Mihalcea et al., 2007) use an English corpus ... See full document
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Semi supervised sequence tagging with bidirectional language models
... general semi-supervised approach for adding pre- trained context embeddings from bidi- rectional language models to NLP sys- tems and apply it to sequence labeling ... See full document
10
Semi Supervised Neural Machine Translation with Language Models
... an approach of transferring knowledge from separately trained language models to translation systems, also we investigate several techniques to improve translation quality when there is a lack of parallel ... See full document
8
EMDC: A Semi supervised Approach for Word Alignment
... For language pairs such as Chinese- English, the word alignment quality is often un- ...considered supervised. Also, a number of semi-supervised word align- ers have been proposed (Taskar et ... See full document
9
Semi supervised Classification of Twitter Messages for Organization Name Disambiguation
... Twitter is an online social networking and microblogging service, which rapidly gained worldwide popularity. How to retrieval, analyze and monitor Twitter information has been receiv- ing a lot of attention in ... See full document
5
Semi Supervised Discriminative Language Modeling with Out of Domain Text Data
... Semi-supervised training for discriminative lan- guage modeling has been shown to achieve as good word error rate (WER) reduction as the training done with real ASR output (Sagae et al., 2012; C ¸ elebi et ... See full document
6
Proceedings of the NAACL HLT 2009 Workshop on Semi supervised Learning for Natural Language Processing
... Will semi-supervised learning (SSL) become the next de-facto standard for building natural language processing (NLP) systems, just as supervised learning has transformed the field in ... See full document
10
Graph Based Semi Supervised Learning for Natural Language Understanding
... Ellie Pavlick, Pushpendre Rastogi, Juri Ganitkevitch, Benjamin Van Durme, and Chris Callison-Burch. 2015. Ppdb 2.0: Better paraphrase ranking, fine- grained entailment relations, word embeddings, and style ... See full document
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Semi Supervised Neural Text Generation by Joint Learning of Natural Language Generation and Natural Language Understanding Models
... The approach of joint learning has been tested in the literature in other domains than NLG/NLU for tasks such machine translation (Cheng et ...on supervised di- alogue ...this approach is competitive ... See full document
11
Fleshing it out: A Supervised Approach to MWE token and MWE type Classification
... Although some multiword expressions (MWEs) like How do you do? have ex- clusively idiomatic meaning, other MWE- types like the phrase kick the bucket may be idiomatic or literal depending on con- text. The recently ... See full document
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