標(biāo)題: Titlebook: Computational Processing of the Portuguese Language; 7th International Wo Renata Vieira,Paulo Quaresma,Maria Carmelita Dias Conference proc [打印本頁(yè)] 作者: 動(dòng)詞 時(shí)間: 2025-3-21 19:54
書目名稱Computational Processing of the Portuguese Language影響因子(影響力)
書目名稱Computational Processing of the Portuguese Language影響因子(影響力)學(xué)科排名
書目名稱Computational Processing of the Portuguese Language網(wǎng)絡(luò)公開(kāi)度
書目名稱Computational Processing of the Portuguese Language網(wǎng)絡(luò)公開(kāi)度學(xué)科排名
書目名稱Computational Processing of the Portuguese Language被引頻次
書目名稱Computational Processing of the Portuguese Language被引頻次學(xué)科排名
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書目名稱Computational Processing of the Portuguese Language年度引用學(xué)科排名
書目名稱Computational Processing of the Portuguese Language讀者反饋
書目名稱Computational Processing of the Portuguese Language讀者反饋學(xué)科排名
作者: 辯論的終結(jié) 時(shí)間: 2025-3-21 20:54 作者: CLAN 時(shí)間: 2025-3-22 00:39 作者: 闡明 時(shí)間: 2025-3-22 08:06
Supply Chain Management with SAP APO?ed. Good experimental results confirmed the adequacy of these techniques to limited-domain tasks. In particular, the reordering algorithm proposed showed impressive improvements by reducing the error rate in excess of 50%.作者: 終端 時(shí)間: 2025-3-22 12:11 作者: 陪審團(tuán)每個(gè)人 時(shí)間: 2025-3-22 16:22
Supply Chain Network Managementstinct strategies to generate its outputs and cooperate to create a global result. This approach allows the use of different strategies and the reduction of errors introduced by individual methods. The cooperation among the agents aims to reach better solutions in each step of the processing.作者: 陪審團(tuán)每個(gè)人 時(shí)間: 2025-3-22 18:00
Modeling and Evaluating Summaries Using Complex Networks that enables easy and fast comparative evaluation of summaries. We evaluate our approach using manually produced summaries and automatic summaries produced by three automatic text summarizers for the Brazilian Portuguese language. The results are in agreement with human intuition and showed to be statistically significant.作者: 向前變橢圓 時(shí)間: 2025-3-22 21:41
,: An Automatic Portuguese Text Summarizer Through Artificial Neural Networks in a More Biologicallyment of more biologically plausible connectionist architecture and training for automatic summarization is emphasized. The choice relies on the expectation that it may lead to an increase in computational efficiency when compared to the so-called biologically implausible algorithms.作者: hegemony 時(shí)間: 2025-3-23 04:59 作者: Incisor 時(shí)間: 2025-3-23 06:28 作者: hurricane 時(shí)間: 2025-3-23 13:11 作者: Lacunar-Stroke 時(shí)間: 2025-3-23 14:42 作者: 愚蠢人 時(shí)間: 2025-3-23 19:25
Panos Kouvelis,Meir J. Rosenblattanged accordingly, adding new rules and applying existing heuristic and disambiguation rules to contextual re-mapping of also lexically . material. In the joint evaluation, PALAVRAS-NER achieved the best overall results, achieving top ranks for both the identification, classification and morphology tasks.作者: muscle-fibers 時(shí)間: 2025-3-24 01:33
Kati Brauer,Wendelin Gro?,Stefan Wolff for training the parser. Our best configuration achieves 80.6% dependency accuracy on unseen test material, well above adjacency baselines and on par with previous results for unlabeled dependencies.作者: Flounder 時(shí)間: 2025-3-24 05:07 作者: 小歌劇 時(shí)間: 2025-3-24 07:34 作者: PET-scan 時(shí)間: 2025-3-24 13:51
Supply Chain Management with SAP APO?luded in traditional gazetteers. We will present some figures regarding the current content of the gazetteer and describe future work regarding the evaluation of this resource and its enrichment with additional information.作者: fluffy 時(shí)間: 2025-3-24 17:31
Supply Chain Management with SAP APO? separated by “natural boundaries”. The results obtained using this method are very close to those obtained using sentence alignment. Some experiments were performed on English-Portuguese and English-Spanish parallel texts.作者: DENT 時(shí)間: 2025-3-24 21:30 作者: 裁決 時(shí)間: 2025-3-25 01:08 作者: 干旱 時(shí)間: 2025-3-25 04:09
https://doi.org/10.1007/978-3-8349-6000-9rom corpora, writing synset concept glosses, and encoding both language-independent conceptual-semantic relations and cross-lingual conceptual-semantic relations between WordNet.Br and Princeton WordNet.作者: DEMN 時(shí)間: 2025-3-25 09:39 作者: Generalize 時(shí)間: 2025-3-25 14:16
REPENTINO – A Wide-Scope Gazetteer for Entity Recognition in Portugueseluded in traditional gazetteers. We will present some figures regarding the current content of the gazetteer and describe future work regarding the evaluation of this resource and its enrichment with additional information.作者: 斷斷續(xù)續(xù) 時(shí)間: 2025-3-25 17:26
Using Natural Alignment to Extract Translation Equivalents separated by “natural boundaries”. The results obtained using this method are very close to those obtained using sentence alignment. Some experiments were performed on English-Portuguese and English-Spanish parallel texts.作者: 飲料 時(shí)間: 2025-3-25 22:20 作者: FLIT 時(shí)間: 2025-3-26 01:28
SIEMêS – A Named-Entity Recognizer for Portuguese Relying on Similarity Ruleslain SIEMêS architecture and its named-entity identification and classification procedure. We also briefly discuss the results of the participation of SIEMêS in HAREM, the named-entity evaluation contest for Portuguese, and describe future work.作者: 貝雷帽 時(shí)間: 2025-3-26 06:32 作者: FER 時(shí)間: 2025-3-26 09:27 作者: nonradioactive 時(shí)間: 2025-3-26 16:38
Adaptation of Data and Models for Probabilistic Parsing of Portuguese for training the parser. Our best configuration achieves 80.6% dependency accuracy on unseen test material, well above adjacency baselines and on par with previous results for unlabeled dependencies.作者: 虛弱 時(shí)間: 2025-3-26 17:59 作者: Inveterate 時(shí)間: 2025-3-26 23:12 作者: Encumber 時(shí)間: 2025-3-27 03:01
,: An Automatic Portuguese Text Summarizer Through Artificial Neural Networks in a More Biologicallartificial neural networks) is presented. Among other contributions that this work intends to bring to natural language processing research, the employment of more biologically plausible connectionist architecture and training for automatic summarization is emphasized. The choice relies on the expec作者: Wordlist 時(shí)間: 2025-3-27 09:08
Building a Dictionary of Anthroponymssource for computational processing, due to the importance of names in the structuring of information in texts. The dictionary has been enriched with morphosyntactic and semantic information. It was then used in the specific task of capitalizing anthroponyms and other proper names on a corpus automa作者: 污點(diǎn) 時(shí)間: 2025-3-27 13:24 作者: Bernstein-test 時(shí)間: 2025-3-27 16:55
Using Natural Alignment to Extract Translation Equivalentshen, they need to get a corpus aligned at the sentence level. Such an alignment can require further manual corrections if the parallel corpus contains insertions, deletions, or fuzzy sentence boundaries. This paper shows that it is possible to extract bilingual lexicons without aligning parallel tex作者: 哎呦 時(shí)間: 2025-3-27 20:43
Open-Source Portuguese–Spanish Machine Translatione . Spanish language pair, developed using the OpenTrad Apertium MT toolbox (.). Apertium uses finite-state transducers for lexical processing, hidden Markov models for part-of-speech tagging, and finite-state-based chunking for structural transfer, and is based on a simple rationale: to produce fas作者: APNEA 時(shí)間: 2025-3-28 01:32
Weighted Finite-State Transducer Inference for Limited-Domain Speech-to-Speech Translationpeech recognition with the machine translation modules. Transducer inference algorithms to automatically learn the translation module are also presented. Good experimental results confirmed the adequacy of these techniques to limited-domain tasks. In particular, the reordering algorithm proposed sho作者: Kindle 時(shí)間: 2025-3-28 04:10
A Golden Resource for Named Entity Recognition in Portugueser named entity recognizers for Portuguese. We discuss the options taken and the originality of our approach compared with previous evaluation initiatives in the area. We document the choice of categories, their quantitative weight in the overall collection and how we deal with vagueness and underspe作者: osteocytes 時(shí)間: 2025-3-28 07:47 作者: Compass 時(shí)間: 2025-3-28 12:05 作者: 試驗(yàn) 時(shí)間: 2025-3-28 15:30
Tools for Nominalization: An Alternative for Lexical Normalization term generation and matching in an information retrieval environment. We present tools that automatically perform nominalization for lexical normalization in Portuguese. Comparing the effects of three alternative strategies (stemming, lemmatizing, and our proposal: nominalization), we demonstrate t作者: Gratulate 時(shí)間: 2025-3-28 20:20
A Framework for Integrating Natural Language Toolsonnected as a chain of filters, apply successive transformations to the data that flows through the system. Hence when integrating such tools, one may face problems that lead to information losses, such as: (i) tools discard information from their input which will be required by other tools further 作者: Lacerate 時(shí)間: 2025-3-28 22:58
Methods and Tools for Encoding the WordNet.Br Sentences, Concept Glosses, and Conceptual-Semantic Reent conceptual-semantic relations (hyponymy, co-hyponymy, meronymy, cause, and entailment) and the so-called cross-lingual conceptual-semantic relations between different wordnets. Accordingly, after contextualizing the project and outlining the current lexical database structure and statistics, it 作者: STERN 時(shí)間: 2025-3-29 06:33 作者: 果仁 時(shí)間: 2025-3-29 09:46 作者: TATE 時(shí)間: 2025-3-29 13:41
A Set of NP-Extraction Rules for Portuguese: Defining, Learning and Pruning machine learned set of transformation rules that was manually reviewed. The noun phrases extracted by these transformations were given as input to another learner that synthesized rules for breaking up complex noun phrases into simpler ones. The results of these processes applied to a Brazilian Por作者: 環(huán)形 時(shí)間: 2025-3-29 15:55 作者: addict 時(shí)間: 2025-3-29 22:28 作者: musicologist 時(shí)間: 2025-3-30 03:55 作者: 卵石 時(shí)間: 2025-3-30 04:17
Supply Chain Management with SAP APO?artificial neural networks) is presented. Among other contributions that this work intends to bring to natural language processing research, the employment of more biologically plausible connectionist architecture and training for automatic summarization is emphasized. The choice relies on the expec作者: DIS 時(shí)間: 2025-3-30 10:21 作者: 土坯 時(shí)間: 2025-3-30 15:23
Supply Chain Management with SAP APO?e. REPENTINO wishes to minimize the problems developers face due to the limited availability of this type of lexical-semantic resources for Portuguese. The data stored in REPENTINO was mostly extracted from corpora and from the web using simple semi-automated methods. Currently, REPENTINO stores nea作者: 主講人 時(shí)間: 2025-3-30 17:21 作者: 換話題 時(shí)間: 2025-3-30 23:51 作者: 燈泡 時(shí)間: 2025-3-31 01:33
Supply Chain Management with SAP APO?peech recognition with the machine translation modules. Transducer inference algorithms to automatically learn the translation module are also presented. Good experimental results confirmed the adequacy of these techniques to limited-domain tasks. In particular, the reordering algorithm proposed sho作者: 施魔法 時(shí)間: 2025-3-31 05:19 作者: AMEND 時(shí)間: 2025-3-31 12:58 作者: 大火 時(shí)間: 2025-3-31 16:20
Christopher S. Tang,Kumar Rajaram,Jihong Ou procedure. These rules try to obtain soft matches between candidate entities found in text and instances contained in a wide-scope gazetteer, and avoid the need for coding large sets of rules by exploiting lexical similarities. Using this matching procedure, SIEMêS generates a set of classification作者: 笨拙的你 時(shí)間: 2025-3-31 17:36
Tonya Boone,Ram Ganeshan,Alan J. Stenger term generation and matching in an information retrieval environment. We present tools that automatically perform nominalization for lexical normalization in Portuguese. Comparing the effects of three alternative strategies (stemming, lemmatizing, and our proposal: nominalization), we demonstrate t作者: Lumbar-Spine 時(shí)間: 2025-3-31 23:43
Christopher S. Tang,Kumar Rajaram,Jihong Ouonnected as a chain of filters, apply successive transformations to the data that flows through the system. Hence when integrating such tools, one may face problems that lead to information losses, such as: (i) tools discard information from their input which will be required by other tools further 作者: Resection 時(shí)間: 2025-4-1 03:22
https://doi.org/10.1007/978-3-8349-6000-9ent conceptual-semantic relations (hyponymy, co-hyponymy, meronymy, cause, and entailment) and the so-called cross-lingual conceptual-semantic relations between different wordnets. Accordingly, after contextualizing the project and outlining the current lexical database structure and statistics, it
