標(biāo)題: Titlebook: Artificial Intelligence and Natural Language; 7th International Co Dmitry Ustalov,Andrey Filchenkov,Jan ?i?ka Conference proceedings 2018 S [打印本頁] 作者: vitamin-D 時間: 2025-3-21 16:03
書目名稱Artificial Intelligence and Natural Language影響因子(影響力)
書目名稱Artificial Intelligence and Natural Language影響因子(影響力)學(xué)科排名
書目名稱Artificial Intelligence and Natural Language網(wǎng)絡(luò)公開度
書目名稱Artificial Intelligence and Natural Language網(wǎng)絡(luò)公開度學(xué)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(xué)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(xué)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(xué)科排名
作者: 星星 時間: 2025-3-22 00:19
A Multi-feature Classifier for Verbal Metaphor Identification in Russian Textsntence length. We combine these features into models of varying complexity; the results of the experiment demonstrate that fairly simple models based on lexical, morphosyntactic and semantic features are able to produce competitive results.作者: 重疊 時間: 2025-3-22 01:41 作者: BRACE 時間: 2025-3-22 07:31 作者: 蟄伏 時間: 2025-3-22 12:34 作者: Toxoid-Vaccines 時間: 2025-3-22 16:24 作者: Lasting 時間: 2025-3-22 18:46
Encyclopedia of Heroism Studiesnducted on a corpus of Russian encyclopaedic texts on linguistics. The results justify applying ESA for this task, and we state that though it works a little inferior to the method based on a search engine in terms of labels’ quality, it can be used as a reasonable alternative because it exhibits two advantages that the baseline method lacks.作者: Notify 時間: 2025-3-22 21:16 作者: 愉快嗎 時間: 2025-3-23 04:43
https://doi.org/10.1007/978-3-031-48129-1 The obtained data on the acoustic features of the speech of TD children can be used as a normative basis in artificial intelligence systems for teaching children, for creating alternative communication systems for children with atypical development, for automatic recognition of child speech.作者: 里程碑 時間: 2025-3-23 06:36
Explicit Semantic Analysis as a Means for Topic Labellingnducted on a corpus of Russian encyclopaedic texts on linguistics. The results justify applying ESA for this task, and we state that though it works a little inferior to the method based on a search engine in terms of labels’ quality, it can be used as a reasonable alternative because it exhibits two advantages that the baseline method lacks.作者: 同謀 時間: 2025-3-23 12:26
A Comparative Study of Publicly Available Russian Sentiment Lexiconsdependence of their F1-measure on their TF-IDF model size. The resulting union lexicon most fully reflects the sentiment lexica of the present day Russian language and can be used both in scientific research and in applied sentiment analysis systems.作者: 十字架 時間: 2025-3-23 17:07 作者: 凈禮 時間: 2025-3-23 20:13
1865-0929 St. Petersburg, Russia, in October 2018. The 19 revised full papers were carefully reviewed and selected from 56 submissions and cover a wide range of topics, including morphology and word-level semantics, sentence and discourse representations, corpus linguistics, language resources, and social int作者: Highbrow 時間: 2025-3-23 22:33
https://doi.org/10.1007/978-3-031-48129-1om LSTM. The aim is to build a model which is simple to implement, light in terms of parameters and works across multiple supervised sentence comparison tasks. We show good results for the model on two sentence comparison datasets.作者: Ibd810 時間: 2025-3-24 03:25
Encyclopedia of Heroism Studiesa confirmation measure and an aggregation function. We designed a regularizer for topic modeling representing this score. The resulting topic modeling method shows significant superiority to all analogs in reflecting human assessments of topic interpretability.作者: etidronate 時間: 2025-3-24 07:28
Supervised Mover’s Distance: A Simple Model for Sentence Comparisonom LSTM. The aim is to build a model which is simple to implement, light in terms of parameters and works across multiple supervised sentence comparison tasks. We show good results for the model on two sentence comparison datasets.作者: 矛盾 時間: 2025-3-24 12:24
Four Keys to Topic Interpretability in Topic Modelinga confirmation measure and an aggregation function. We designed a regularizer for topic modeling representing this score. The resulting topic modeling method shows significant superiority to all analogs in reflecting human assessments of topic interpretability.作者: LIKEN 時間: 2025-3-24 15:23
Conference proceedings 2018burg, Russia, in October 2018. The 19 revised full papers were carefully reviewed and selected from 56 submissions and cover a wide range of topics, including morphology and word-level semantics, sentence and discourse representations, corpus linguistics, language resources, and social interaction a作者: PANT 時間: 2025-3-24 19:37 作者: 直言不諱 時間: 2025-3-25 01:02 作者: 易于出錯 時間: 2025-3-25 04:28 作者: 瑣事 時間: 2025-3-25 07:47 作者: 撫育 時間: 2025-3-25 15:28
Encyclopedia of Heroism Studiesth, heart failure and chronic liver diseases (cirrhosis and fibrosis) prediction tasks. We propose ontology-based regularization method that can be used to pre-train MCV embeddings. The approach we use to predict these diseases and conditions can be applied to solve other prediction tasks.作者: 葡萄糖 時間: 2025-3-25 16:12 作者: 謙卑 時間: 2025-3-25 21:26
A Multi-feature Classifier for Verbal Metaphor Identification in Russian TextsRussian text. We introduce the custom-created training dataset, describe the feature engineering techniques, and discuss the results. The following set of features is applied: distributional semantic features, lexical and morphosyntactic co-occurrence frequencies, flag words, quotation marks, and se作者: 擦試不掉 時間: 2025-3-26 01:27 作者: condone 時間: 2025-3-26 06:17
Named Entity Recognition in Russian with Word Representation Learned by a Bidirectional Language Modhave become a standard component of neural network architectures for natural language processing tasks. However, in most cases, a recurrent network that operates on word-level representations to produce context sensitive representations is trained on relatively few labeled data. Also, there are many作者: 有害 時間: 2025-3-26 11:58
Supervised Mover’s Distance: A Simple Model for Sentence Comparisonory (LSTM) through a Relation Network. The Relation Network module tries to extract similarity between multiple contextual representations obtained from LSTM. The aim is to build a model which is simple to implement, light in terms of parameters and works across multiple supervised sentence comparis作者: Cloudburst 時間: 2025-3-26 14:02 作者: voluble 時間: 2025-3-26 17:37 作者: 農(nóng)學(xué) 時間: 2025-3-26 21:09
Avoiding Echo-Responses in a Retrieval-Based Conversation System context. While the system’s goal is to find the most appropriate response, rather than the most semantically similar one, this tendency results in low-quality responses. We refer to this challenge as the echoing problem. To mitigate this problem, we utilize a hard negative mining approach at the tr作者: 沉著 時間: 2025-3-27 01:10 作者: humectant 時間: 2025-3-27 07:46
Explicit Semantic Analysis as a Means for Topic Labellingut, and the algorithm yields titles of Wikipedia articles that are considered most relevant to the input. An alternative approach that serves as a strong baseline employs titles of first outputs in a search engine, given topic words as a query. In both methods, obtained titles are then automatically作者: Bouquet 時間: 2025-3-27 10:51 作者: 津貼 時間: 2025-3-27 16:25
Cleaning Up After a Party: Post-processing Thesaurus Crowdsourced Dataays. Second, we apply four cluster cleaning techniques based either on word popularity or word embeddings. Evaluation shows that the method based on word embeddings and existing dictionary definitions delivers best results.作者: enflame 時間: 2025-3-27 19:01 作者: construct 時間: 2025-3-27 23:21
Acoustic Features of Speech of Typically Developing Children Aged 5–16 Yearsf the study is to describe the dynamics of the temporal and spectral characteristics of the words of 5–16 years old children depending on their gender and age. The decrease of stressed and unstressed vowels duration from child’s words to the age of 13 years is revealed. Pitch values of vowels from w作者: MOAT 時間: 2025-3-28 04:21
Named Entity Recognition in Russian with Word Representation Learned by a Bidirectional Language Modext corpus. We show that these representations can be easily added to existing models and be combined with other word representation features. We evaluate our model on FactRuEval-2016 dataset for named entity recognition in Russian and achieve state of the art results.作者: ALTER 時間: 2025-3-28 07:18 作者: 拋媚眼 時間: 2025-3-28 10:54 作者: 生銹 時間: 2025-3-28 15:51
Encyclopedia of Heroism Studiest the sentence beginning or after a comma. Secondly, we build multi-word tokens that are based on these patterns. Thirdly, we build vector representations for the multi-word tokens that match these patterns. Our experiments based on distributional semantics give quite reasonable list of the candidat作者: 羊欄 時間: 2025-3-28 21:01
Communications in Computer and Information Sciencehttp://image.papertrans.cn/b/image/162258.jpg作者: Aggrandize 時間: 2025-3-28 23:39 作者: rheumatism 時間: 2025-3-29 06:59 作者: indecipherable 時間: 2025-3-29 10:00 作者: pulmonary-edema 時間: 2025-3-29 11:32
https://doi.org/10.1007/978-3-030-01204-5artificial intelligence; crowdsourcing; discourse, dialogue and pragmatics; information extraction; info作者: 著名 時間: 2025-3-29 18:03 作者: musicologist 時間: 2025-3-29 22:00
Jie Wang,Wenye Wang,Xiaogang Wanglem still remains fairly untouched for Russian. In this article we present a novel approach to Disambiguation to Wikipedia applied to the Russian language. Inspired by the Neural Machine Translation task our method implements encoder-decoder neural network architecture. It translates text tokens int作者: 焦慮 時間: 2025-3-30 03:08
Encrypted Network Traffic AnalysisRussian text. We introduce the custom-created training dataset, describe the feature engineering techniques, and discuss the results. The following set of features is applied: distributional semantic features, lexical and morphosyntactic co-occurrence frequencies, flag words, quotation marks, and se作者: 馬具 時間: 2025-3-30 05:49 作者: Alopecia-Areata 時間: 2025-3-30 10:30
Encyclopedia of Heroism Studieshave become a standard component of neural network architectures for natural language processing tasks. However, in most cases, a recurrent network that operates on word-level representations to produce context sensitive representations is trained on relatively few labeled data. Also, there are many作者: 整潔 時間: 2025-3-30 13:10 作者: 新奇 時間: 2025-3-30 16:42
Encyclopedia of Heroism Studiesity to improve translation quality in the case of Persian-Spanish low-resource language pair using a well-resource language such as English as the bridge one. We apply the optimized direct-bridge combination scenario to enhance the translation performance. We analyze the effects of this scenario on 作者: ostensible 時間: 2025-3-30 21:20 作者: triptans 時間: 2025-3-31 03:01
