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: Information Retrieval and Natural Language Processing; A Graph Theory Appro Sheetal S. Sonawane,Parikshit N. Mahalle,Archana S Book 2022 Th

[復(fù)制鏈接]
查看: 6163|回復(fù): 43
樓主
發(fā)表于 2025-3-21 17:47:36 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Information Retrieval and Natural Language Processing
副標(biāo)題A Graph Theory Appro
編輯Sheetal S. Sonawane,Parikshit N. Mahalle,Archana S
視頻videohttp://file.papertrans.cn/466/465221/465221.mp4
概述Provides a comprehensive view of graph theory in informational retrieval and natural language processing.Details understanding of graph theory basics, graph algorithms and networks using graph.Serves
叢書名稱Studies in Big Data
圖書封面Titlebook: Information Retrieval and Natural Language Processing; A Graph Theory Appro Sheetal S. Sonawane,Parikshit N. Mahalle,Archana S Book 2022 Th
描述.This book gives a comprehensive view of graph theory in informational retrieval (IR) and natural language processing(NLP). This book provides number of graph techniques for IR and NLP applications with examples. It also provides understanding of graph theory basics, graph algorithms and networks using graph. The book is divided into three parts and contains nine chapters. The first part gives graph theory basics and graph networks, and the second part provides basics of IR with graph-based information retrieval. The third part covers IR and NLP recent and emerging applications with case studies using graph theory. ..This book is unique in its way as it provides a strong foundation to a beginner in applying mathematical structure graph for IR and NLP applications. All technical details that include tools and technologies used for graph algorithms and implementation in Information Retrieval and Natural Language Processing with its future scope are explained in a clear and organized format..
出版日期Book 2022
關(guān)鍵詞Graph Theory; Graph methods; Natural Language Processing; Information Retrieval; Data Science; Text Analy
版次1
doihttps://doi.org/10.1007/978-981-16-9995-5
isbn_softcover978-981-16-9997-9
isbn_ebook978-981-16-9995-5Series ISSN 2197-6503 Series E-ISSN 2197-6511
issn_series 2197-6503
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapor
The information of publication is updating

書目名稱Information Retrieval and Natural Language Processing影響因子(影響力)




書目名稱Information Retrieval and Natural Language Processing影響因子(影響力)學(xué)科排名




書目名稱Information Retrieval and Natural Language Processing網(wǎng)絡(luò)公開度




書目名稱Information Retrieval and Natural Language Processing網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Information Retrieval and Natural Language Processing被引頻次




書目名稱Information Retrieval and Natural Language Processing被引頻次學(xué)科排名




書目名稱Information Retrieval and Natural Language Processing年度引用




書目名稱Information Retrieval and Natural Language Processing年度引用學(xué)科排名




書目名稱Information Retrieval and Natural Language Processing讀者反饋




書目名稱Information Retrieval and Natural Language Processing讀者反饋學(xué)科排名




單選投票, 共有 1 人參與投票
 

1票 100.00%

Perfect with Aesthetics

 

0票 0.00%

Better Implies Difficulty

 

0票 0.00%

Good and Satisfactory

 

0票 0.00%

Adverse Performance

 

0票 0.00%

Disdainful Garbage

您所在的用戶組沒有投票權(quán)限
沙發(fā)
發(fā)表于 2025-3-21 21:59:32 | 只看該作者
板凳
發(fā)表于 2025-3-22 01:15:19 | 只看該作者
地板
發(fā)表于 2025-3-22 04:34:25 | 只看該作者
5#
發(fā)表于 2025-3-22 09:00:35 | 只看該作者
Text Document Pre-processing Using Graph Theoryre-processing algorithms are explained in the chapter with examples. The graph characteristics, properties, and operations useful to solve document preprocessing task is well explained in this chapter, The tools/libraries available are also provided in last section of the chapter.
6#
發(fā)表于 2025-3-22 15:22:08 | 只看該作者
7#
發(fā)表于 2025-3-22 20:30:37 | 只看該作者
8#
發(fā)表于 2025-3-23 00:00:26 | 只看該作者
9#
發(fā)表于 2025-3-23 01:59:38 | 只看該作者
Text Analytics Using Graph Theoryhism is discussed in this chapter. The concept of term weighting in graph with generating extractive and abstractive summary by using graph operations is well explained with different graph types and properties. The applications like question answer system, sentiment analysis and recommendation syst
10#
發(fā)表于 2025-3-23 06:28:28 | 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, 2026-2-9 08:21
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
临潭县| 阳春市| 宿松县| 奎屯市| 石河子市| 金湖县| 沙河市| 嫩江县| 丰县| 江达县| 特克斯县| 鹤壁市| 迁西县| 武城县| 铁岭市| 叶城县| 泗洪县| 大名县| 通辽市| 普宁市| 张家口市| 江油市| 牡丹江市| 文成县| 临高县| 阜平县| 漠河县| 上犹县| 临高县| 罗山县| 焦作市| 吉水县| 建昌县| 灵石县| 乳山市| 德州市| 大同县| 温宿县| 库尔勒市| 辽阳县| 铁力市|