找回密碼
 To register

QQ登錄

只需一步,快速開始

掃一掃,訪問微社區(qū)

打印 上一主題 下一主題

Titlebook: Artificial Intelligence and Natural Language; 7th International Co Dmitry Ustalov,Andrey Filchenkov,Jan ?i?ka Conference proceedings 2018 S

[復(fù)制鏈接]
樓主: vitamin-D
11#
發(fā)表于 2025-3-23 12:26:34 | 只看該作者
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.
12#
發(fā)表于 2025-3-23 17:07:21 | 只看該作者
13#
發(fā)表于 2025-3-23 20:13:39 | 只看該作者
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
14#
發(fā)表于 2025-3-23 22:33:35 | 只看該作者
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.
15#
發(fā)表于 2025-3-24 03:25:17 | 只看該作者
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.
16#
發(fā)表于 2025-3-24 07:28:19 | 只看該作者
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.
17#
發(fā)表于 2025-3-24 12:24:14 | 只看該作者
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.
18#
發(fā)表于 2025-3-24 15:23:53 | 只看該作者
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
19#
發(fā)表于 2025-3-24 19:37:43 | 只看該作者
20#
發(fā)表于 2025-3-25 01:02:15 | 只看該作者
 關(guān)于派博傳思  派博傳思旗下網(wǎng)站  友情鏈接
派博傳思介紹 公司地理位置 論文服務(wù)流程 影響因子官網(wǎng) 吾愛論文網(wǎng) 大講堂 北京大學(xué) Oxford Uni. Harvard Uni.
發(fā)展歷史沿革 期刊點(diǎn)評(píng) 投稿經(jīng)驗(yàn)總結(jié) SCIENCEGARD IMPACTFACTOR 派博系數(shù) 清華大學(xué) Yale Uni. Stanford Uni.
QQ|Archiver|手機(jī)版|小黑屋| 派博傳思國(guó)際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-13 02:26
Copyright © 2001-2015 派博傳思   京公網(wǎng)安備110108008328 版權(quán)所有 All rights reserved
快速回復(fù) 返回頂部 返回列表
怀集县| 揭东县| 固阳县| 雅江县| 瓦房店市| 沧源| 普陀区| 甘孜县| 上高县| 望奎县| 新乡县| 徐州市| 游戏| 格尔木市| 衢州市| 高邮市| 贵南县| 永康市| 扶沟县| 安西县| 宜黄县| 临沧市| 吐鲁番市| 曲周县| 修武县| 南阳市| 广丰县| 武隆县| 新源县| 高雄县| 滦平县| 庆元县| 遂昌县| 高平市| 兴安盟| 长泰县| 乌兰浩特市| 临泉县| 纳雍县| 乌鲁木齐市| 湖南省|