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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 3 4 Hits 1 – 20 of 79 1 Parallel processing in speech perception with local and global representations of linguistic context Brodbeck, Christian; Bhattasali, Shohini; Cruz Heredia, Aura AL... In: eLife (2022) BASE Show details 2 Using surprisal and fMRI to map the neural bases of broad and local contextual prediction during natural language comprehension ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Bhattasali, Shohini; Resnik, Philip. - : Underline Science Inc., 2021 BASE Show details 3 Community-level Research on Suicidality Prediction in a Secure Environment: Overview of the CLPsych 2021 Shared Task MacAvaney, Sean; Mittu, Anjali; Coppersmith, Glen. - 2021 BASE Show details 4 Connecting Documents, Words, and Languages Using Topic Models Yang, Weiwei. - 2019 Abstract: Topic models discover latent topics in documents and summarize documents at a high level. To improve topic models' topic quality and extrinsic performance, external knowledge is often incorporated as part of the generative story. One form of external knowledge is weighted text links that indicate similarity or relatedness between the connected objects. This dissertation 1) uncovers the latent structures in observed weighted links and integrates them into topic modeling, and 2) learns latent weighted links from other external knowledge to improve topic modeling. We consider incorporating links at three different levels: documents, words, and topics. We first look at binary document links, e.g., citation links of papers. Document links indicate topic similarity of the connected documents. Past methods model the document links separately, ignoring the entire link density. We instead uncover latent document blocks in which documents are densely connected and tend to talk about similar topics. We introduce LBH-RTM, a relational topic model with lexical weights, block priors, and hinge loss. It extracts informative topic priors from the document blocks for documents' topic generation. It predicts unseen document links with block and lexical features and hinge loss, in addition to topical features. It outperforms past methods in link prediction and gives more coherent topics. Like document links, words are also linked, but usually with real-valued weights. Word links are known as word associations and indicate the semantic relatedness of the connected words. They provide more information about word relationships in addition to the co-occurrence patterns in the training corpora. To extract and incorporate the knowledge in word associations, we introduce methods to find the most salient word pairs. The methods organize the words in a tree structure, which serves as a prior (i.e., tree prior) for tree LDA. The methods are straightforward but effective, yielding more coherent topics than vanilla LDA, and slightly improving the extrinsic classification performance. Weighted topic links are different. Topics are latent, so it is difficult to obtain ground-truth topic links, but learned weighted topic links could bridge the topics across languages. We introduce a multilingual topic model (MTM) that assumes each language has its own topic distributions over the words only in that language and learns weighted topic links based on word translations and words' topic distributions. It does not force the topic spaces of different languages to be aligned and is more robust than previous MTMs that do. It outperforms past MTMs in classification while still giving coherent topics on less comparable and smaller corpora. Keyword: Artificial intelligence; Computer science; Topic Model URL: http://hdl.handle.net/1903/25003 https://doi.org/10.13016/jiwk-1bh3 BASE Hide details 5 Assessing Composition in Sentence Vector Representations ... Ettinger, Allyson; Elgohary, Ahmed; Phillips, Colin. - : arXiv, 2018 BASE Show details 6 Relating lexical and syntactic processes in language: Bridging research in humans and machines Ettinger, Allyson. - 2018 BASE Show details 7 Guided Probabilistic Topic Models for Agenda-setting and Framing Nguyen, Viet An. - 2015 BASE Show details 8 Soft syntactic constraints for Arabic-English hierarchical phrase-based translation Resnik, Philip; Chiang, David; Marton, Yuval In: Machine translation. - Dordrecht [u.a.] : Springer Science + Business Media 26 (2012) 1-2, 137-157 BLLDB OLC Linguistik Show details 9 Crowdsourced Monolingual Translation Hu, Chang. - 2012 BASE Show details 10 Decision Tree-based Syntactic Language Modeling Filimonov, Denis. - 2011 BASE Show details 11 Modeling Dependencies in Natural Languages with Latent Variables Huang, Zhongqiang. - 2011 BASE Show details 12 Exploiting syntactic relationships in a phrase-based decoder: an exploration Hunter, Tim; Resnik, Philip In: Machine translation. - Dordrecht [u.a.] : Springer Science + Business Media 24 (2010) 2, 123-140 BLLDB OLC Linguistik Show details 13 Gibbs Sampling for the Uninitiated Resnik, Philip; Hardisty, Eric In: DTIC (2010) BASE Show details 14 Structured local exponential models for machine translation Subotin, Michael. - 2010 BASE Show details 15 A Formal Model of Ambiguity and its Applications in Machine Translation Dyer, Christopher. - 2010 BASE Show details 16 Extending Phrase-Based Decoding with a Dependency-Based Reordering Model Hunter, Tim; Resnik, Philip In: DTIC (2009) BASE Show details 17 Extending Phrase-Based Decoding with a Dependency-Based Reordering Model Resnik, Philip; Hunter, Tim. - 2009 BASE Show details 18 COMPUTATIONAL ANALYSIS OF THE CONVERSATIONAL DYNAMICS OF THE UNITED STATES SUPREME COURT Hawes, Timothy. - 2009 BASE Show details 19 Fine-Grained Linguistic Soft Constraints on Statistical Natural Language Processing Models Marton, Yuval Yehezkel. - 2009 BASE Show details 20 Generalizing Word Lattice Translation Dyer, Christopher; Muresan, Smaranda; Resnik, Philip In: DTIC (2008) BASE Show details Page: 1 2 3 4

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