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: Web and Big Data; First International Lei Chen,Christian S. Jensen,Xiang Lian Conference proceedings 2017 Springer International Publishin

[復(fù)制鏈接]
樓主: Lensometer
41#
發(fā)表于 2025-3-28 17:35:01 | 只看該作者
Keyphrase Extraction Using Knowledge GraphsAlthough lots of efforts have been made on keyphrase extraction, most of the existing methods (the co-occurrence based methods and the statistic-based methods) do not take semantics into full consideration. The co-occurrence based methods heavily depend on the co-occurrence relations between two wor
42#
發(fā)表于 2025-3-28 20:02:56 | 只看該作者
Keyphrase Extraction Using Knowledge GraphsAlthough lots of efforts have been made on keyphrase extraction, most of the existing methods (the co-occurrence based methods and the statistic-based methods) do not take semantics into full consideration. The co-occurrence based methods heavily depend on the co-occurrence relations between two wor
43#
發(fā)表于 2025-3-29 00:02:41 | 只看該作者
Semantic-Aware Partitioning on RDF Graphsficiently process complex queries on RDF graphs. It becomes necessary to use a distributed cluster to store and process large-scale RDF datasets that are required to be partitioned. In this paper, we propose a . method for RDF graphs. Inspired by the . algorithm, classes in the RDF . are ranked. A n
44#
發(fā)表于 2025-3-29 06:38:11 | 只看該作者
Semantic-Aware Partitioning on RDF Graphsficiently process complex queries on RDF graphs. It becomes necessary to use a distributed cluster to store and process large-scale RDF datasets that are required to be partitioned. In this paper, we propose a . method for RDF graphs. Inspired by the . algorithm, classes in the RDF . are ranked. A n
45#
發(fā)表于 2025-3-29 07:56:18 | 只看該作者
An Incremental Algorithm for Estimating Average Clustering Coefficient Based on Random Walko compute clustering coefficient for the real-world networks, because many networks, such as Facebook and Twitter, are usually large and evolving continuously. Aiming to improve the performance of clustering coefficient computation for the large and evolving networks, we propose an incremental algor
46#
發(fā)表于 2025-3-29 12:15:25 | 只看該作者
47#
發(fā)表于 2025-3-29 16:16:51 | 只看該作者
48#
發(fā)表于 2025-3-29 21:03:46 | 只看該作者
Deep Multi-label Hashing for Large-Scale Visual Search Based on Semantic Graphhem with their friends. Accordingly, visual search from large scale image databases is getting more and more important. Hashing is an efficient technique to large-scale visual content search, and learning-based hashing approaches have achieved great success due to recent advancements of deep learnin
49#
發(fā)表于 2025-3-30 00:35:22 | 只看該作者
50#
發(fā)表于 2025-3-30 07:40:14 | 只看該作者
An Ontology-Based Latent Semantic Indexing Approach Using Long Short-Term Memory Networkseen widely used to optimize performance. However, researchers are placing increased emphasis on internal relations of ontologies but neglect latent semantic relations between ontologies and documents. They generally annotate instances mentioned in documents, which are related to concepts in ontologi
 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 投稿經(jīng)驗總結(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| 派博傳思國際 ( 京公網(wǎng)安備110108008328) GMT+8, 2025-10-7 12:38
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
建昌县| 镇坪县| 万全县| 建宁县| 色达县| 区。| 霸州市| 白银市| 类乌齐县| 高雄县| 丰顺县| 大宁县| 上栗县| 扎赉特旗| 年辖:市辖区| 荥阳市| 鹤岗市| 保定市| 南木林县| 高尔夫| 古丈县| 井冈山市| 定远县| 田林县| 扬州市| 磐石市| 博野县| 长汀县| 安泽县| 集贤县| 西乌| 广丰县| 灌云县| 浮山县| 定结县| 社旗县| 邹城市| 弥勒县| 鄄城县| 峨边| 元阳县|