書目名稱Artificial Intelligence and Natural Language影響因子(影響力)學科排名
書目名稱Artificial Intelligence and Natural Language網(wǎng)絡公開度
書目名稱Artificial Intelligence and Natural Language網(wǎng)絡公開度學科排名
書目名稱Artificial Intelligence and Natural Language被引頻次
書目名稱Artificial Intelligence and Natural Language被引頻次學科排名
書目名稱Artificial Intelligence and Natural Language年度引用
書目名稱Artificial Intelligence and Natural Language年度引用學科排名
書目名稱Artificial Intelligence and Natural Language讀者反饋
書目名稱Artificial Intelligence and Natural Language讀者反饋學科排名
作者: 機械 時間: 2025-3-22 00:02 作者: 蝕刻 時間: 2025-3-22 01:58 作者: archaeology 時間: 2025-3-22 06:40
Artificial Intelligence and Natural Language978-3-030-59082-6Series ISSN 1865-0929 Series E-ISSN 1865-0937 作者: 創(chuàng)新 時間: 2025-3-22 11:25
Proze?phasen von lernenden FuE-KooperationenThe task for participants was to train a general-purpose MT system which performs reasonably well on very diverse text domains and styles without additional fine-tuning. 11 teams participated in the competition, some of the submitted models showed reasonably good performance topping at ..作者: Oafishness 時間: 2025-3-22 14:15 作者: Talkative 時間: 2025-3-22 18:32
Encyclopedia of Heroism Studiesand political issues. The lexicon was generated from a database of posts and comments of the top 2,000 LiveJournal bloggers posted during one year (.1.5 million posts and 20 million comments). Following a topic modeling approach, we extracted 85,898 documents that were used to retrieve domain-specif作者: 饒舌的人 時間: 2025-3-23 01:15
Encyclopedia of Heroism Studiesposts. Modern algorithms for hidden community detection are based on graph theory, these procedures leaving out of account the linguistic features of analyzed texts. The authors have developed a new hybrid approach to the detection of hidden communities, combining author-topic modeling and automatic作者: 一致性 時間: 2025-3-23 03:59 作者: LATE 時間: 2025-3-23 07:18
Implikationen der Untersuchung,s, question answering, named entity recognition. Headline generation is a special kind of text summarization task. Models need to have strong natural language understanding that goes beyond the meaning of individual words and sentences and an ability to distinguish essential information to succeed i作者: addict 時間: 2025-3-23 11:22 作者: extract 時間: 2025-3-23 13:53 作者: 發(fā)芽 時間: 2025-3-23 19:32 作者: exercise 時間: 2025-3-23 22:40
Alois Haas,Dieter Koschel,Ulrich Niemannt evaluation datasets. We compare two variants of Russian BERT and show that for all sentiment tasks in this study the conversational variant of Russian BERT performs better. The best results were achieved by BERT-NLI model, which treats sentiment classification tasks as a natural language inference作者: conformity 時間: 2025-3-24 04:37 作者: 商談 時間: 2025-3-24 09:38
https://doi.org/10.1007/978-3-662-06321-7istic templates. We translate the linguistic templates to Russian leaving the inference part without changes. So as a result we get a mathematically parallel dataset where the same mathematical problems are explored but in another language. We reproduce the experiment from the original paper to chec作者: GOAT 時間: 2025-3-24 14:24
https://doi.org/10.1007/978-3-662-06318-7aw. The novelty of the work comes from the idea of using legal documents for automatic formulation of the query, including case law judgments, legal case descriptions, or other texts. The query documents may be in various formats, including image files with text content. This approach allows efficie作者: Compass 時間: 2025-3-24 17:46
https://doi.org/10.1007/978-3-662-06318-7 SSL algorithms use a default adjacency matrix with binary weights on edges (citations), that causes a loss of the nodes (papers) similarity information. In this work, therefore, we propose a framework focused on embedding PageRank SSL in a generative model. This framework allows one to do joint tra作者: 絆住 時間: 2025-3-24 21:31
F&E-Kooperationen im Mittelstand context, distributional measures) can efficiently detect the most prominent MWEs. However, given a large number of MWEs already present in a lexical resource those methods fail to provide sufficient results in extracting unseen expressions. We show that the information deduced from the thesaurus it作者: Archipelago 時間: 2025-3-25 02:18
F&E-Kooperationen im Mittelstandch instruments is Linguistic Inquiry and Word Count, which was compiled manually in English and translated into many other languages. We argue that the resource contains a lot of subjectivity, which is further increased in the translation process. As a result, the translated lexical resource is not 作者: 可商量 時間: 2025-3-25 06:08
Proze?phasen von lernenden FuE-KooperationenThe task for participants was to train a general-purpose MT system which performs reasonably well on very diverse text domains and styles without additional fine-tuning. 11 teams participated in the competition, some of the submitted models showed reasonably good performance topping at ..作者: 打谷工具 時間: 2025-3-25 09:41 作者: 輕信 時間: 2025-3-25 11:40 作者: Intervention 時間: 2025-3-25 15:50 作者: muscle-fibers 時間: 2025-3-25 23:40
Advances of Transformer-Based Models for News Headline Generation,s, question answering, named entity recognition. Headline generation is a special kind of text summarization task. Models need to have strong natural language understanding that goes beyond the meaning of individual words and sentences and an ability to distinguish essential information to succeed i作者: 戲法 時間: 2025-3-26 00:46
An Explanation Method for Black-Box Machine Learning Survival Models Using the Chebyshev Distance,behind SurvLIME as well as SurvLIME-Inf is to apply the Cox proportional hazards model to approximate the black-box survival model at the local area around a test example. The Cox model is used due to the linear relationship of covariates. In contrast to SurvLIME, the proposed modification uses .-no作者: 扔掉掐死你 時間: 2025-3-26 06:24 作者: Commonplace 時間: 2025-3-26 09:47
Predicting Eurovision Song Contest Results Using Sentiment Analysis,thods of sentiment analysis (English, multilingual polarity lexicons and deep learning) and translating the focus language tweets into English were used to determine the method that produced the best prediction for the contest. Furthermore, we analyzed the effect of sampling tweets during different 作者: DOSE 時間: 2025-3-26 16:27 作者: Custodian 時間: 2025-3-26 19:01 作者: clarify 時間: 2025-3-27 00:33 作者: Latency 時間: 2025-3-27 02:28
Searching Case Law Judgments by Using Other Judgments as a Query,aw. The novelty of the work comes from the idea of using legal documents for automatic formulation of the query, including case law judgments, legal case descriptions, or other texts. The query documents may be in various formats, including image files with text content. This approach allows efficie作者: 合乎習俗 時間: 2025-3-27 05:58
GenPR: Generative PageRank Framework for Semi-supervised Learning on Citation Graphs, SSL algorithms use a default adjacency matrix with binary weights on edges (citations), that causes a loss of the nodes (papers) similarity information. In this work, therefore, we propose a framework focused on embedding PageRank SSL in a generative model. This framework allows one to do joint tra作者: Alopecia-Areata 時間: 2025-3-27 12:22
Finding New Multiword Expressions for Existing Thesaurus, context, distributional measures) can efficiently detect the most prominent MWEs. However, given a large number of MWEs already present in a lexical resource those methods fail to provide sufficient results in extracting unseen expressions. We show that the information deduced from the thesaurus it作者: Between 時間: 2025-3-27 17:24 作者: fallible 時間: 2025-3-27 20:09 作者: Maximize 時間: 2025-3-28 01:26
Conference proceedings 2020ume presents 1 shared task paper. The volume presents recent research in areas of?of text mining, speech technologies, dialogue systems, information retrieval, machine learning, articial intelligence, and robotics.?.作者: Humble 時間: 2025-3-28 04:03
1865-0929 y, the volume presents 1 shared task paper. The volume presents recent research in areas of?of text mining, speech technologies, dialogue systems, information retrieval, machine learning, articial intelligence, and robotics.?.978-3-030-59081-9978-3-030-59082-6Series ISSN 1865-0929 Series E-ISSN 1865-0937 作者: 使害羞 時間: 2025-3-28 08:49
Encyclopedia of Heroism Studies topic labeling. Specific linguistic parameters of Russian posts were revealed for correct language processing. The results justify the use of the algorithm that can be further integrated with already developed graph methods.作者: Scintigraphy 時間: 2025-3-28 11:09
https://doi.org/10.1007/978-3-662-06321-7k whether the performance of a Transformer model is impacted by the differences of the languages in which math problems are expressed. Though our contribution is small compared to the original work, we think it is valuable given the fact that languages other than English (and Russian in particular) are underrepresented.作者: 無法破譯 時間: 2025-3-28 18:01 作者: 爭吵加 時間: 2025-3-28 22:39 作者: 神圣在玷污 時間: 2025-3-29 02:10 作者: 動物 時間: 2025-3-29 03:22
https://doi.org/10.1007/978-3-662-06318-7plain that a generative model can improve accuracy and reduce the number of iteration steps for PageRank SSL. Moreover, we show that our framework outperforms the best graph-based SSL algorithms on four public citation graph data sets and improves the interpretability of classification results.作者: LAIR 時間: 2025-3-29 08:17 作者: 辮子帶來幫助 時間: 2025-3-29 11:33
Advances of Transformer-Based Models for News Headline Generation,s on the RIA and Lenta datasets of Russian news. BertSumAbs increases ROUGE on average by 2.9 and 2.0 points respectively over previous best score achieved by Phrase-Based Attentional Transformer and CopyNet.作者: insular 時間: 2025-3-29 16:05
An Explanation Method for Black-Box Machine Learning Survival Models Using the Chebyshev Distance,termining important features and for explaining the black-box model prediction. Moreover, SurvLIME-Inf outperforms SurvLIME when the training set is very small. Numerical experiments with synthetic and real datasets demonstrate the SurvLIME-Inf efficiency.作者: Handedness 時間: 2025-3-29 22:12
Unsupervised Neural Aspect Extraction with Related Terms,demonstrate the effectiveness on the real-world dataset. We apply a special loss aimed to improve the quality of multi-aspect extraction. The experimental study demonstrates, what with this loss we increase the precision not only on this joint setting but also on aspect prediction only.作者: triptans 時間: 2025-3-30 00:23 作者: 令人苦惱 時間: 2025-3-30 05:14 作者: 希望 時間: 2025-3-30 11:06
Automatic Detection of Hidden Communities in the Texts of Russian Social Network Corpus, topic labeling. Specific linguistic parameters of Russian posts were revealed for correct language processing. The results justify the use of the algorithm that can be further integrated with already developed graph methods.作者: 綁架 時間: 2025-3-30 12:25 作者: Anguish 時間: 2025-3-30 17:27
Conference proceedings 2020nland, in October 2020.?.The 11 revised full papers and 3 short papers were carefully reviewed and selected from 36 submissions. Additionally, the volume presents 1 shared task paper. The volume presents recent research in areas of?of text mining, speech technologies, dialogue systems, information r作者: observatory 時間: 2025-3-31 00:10
Alois Haas,Dieter Koschel,Ulrich Niemannlevoting scoring system to the results of the sentiment analysis of tweets. A predicted rank for each performance resulted in a Spearman . correlation coefficients of 0.62 and 0.74 during the televoting period for the lexicon sentiment-based and deep learning approaches, respectively.作者: VALID 時間: 2025-3-31 02:41
https://doi.org/10.1007/978-3-662-06318-7 the approach for document relevance ranking has been evaluated using a gold standard set of inter-document similarities. We show that a linear combination of similarities derived from the individual models provides a robust automatic similarity assessment for ranking the case law documents for retrieval.
