標(biāo)題: Titlebook: Web-Age Information Management; 17th International C Bin Cui,Nan Zhang,Dexi Liu Conference proceedings 2016 Springer International Publishi [打印本頁] 作者: 老鼠系領(lǐng)帶 時間: 2025-3-21 18:50
書目名稱Web-Age Information Management影響因子(影響力)
書目名稱Web-Age Information Management影響因子(影響力)學(xué)科排名
書目名稱Web-Age Information Management網(wǎng)絡(luò)公開度
書目名稱Web-Age Information Management網(wǎng)絡(luò)公開度學(xué)科排名
書目名稱Web-Age Information Management被引頻次
書目名稱Web-Age Information Management被引頻次學(xué)科排名
書目名稱Web-Age Information Management年度引用
書目名稱Web-Age Information Management年度引用學(xué)科排名
書目名稱Web-Age Information Management讀者反饋
書目名稱Web-Age Information Management讀者反饋學(xué)科排名
作者: 猜忌 時間: 2025-3-21 20:48
https://doi.org/10.1007/978-3-319-39937-9cloud computing; distributed system; internet of things; semantic network; active learning; algorithm; cro作者: 重疊 時間: 2025-3-22 02:35
Bin Cui,Nan Zhang,Dexi LiuIncludes supplementary material: 作者: Excise 時間: 2025-3-22 06:05
978-3-319-39936-2Springer International Publishing Switzerland 2016作者: 賞心悅目 時間: 2025-3-22 09:06
Web-Age Information Management978-3-319-39937-9Series ISSN 0302-9743 Series E-ISSN 1611-3349 作者: set598 時間: 2025-3-22 14:05
Discovering Underground Roads from Trajectories Without Road Network framework to deal with the issues, including an incremental clustering phase, a sub-trajectory detecting phase and a cluster filtering phase. Experiments upon real-life data sets demonstrate the effectiveness and efficiency of the proposed framework.作者: 暗指 時間: 2025-3-22 19:22
Discovering Underground Roads from Trajectories Without Road Network framework to deal with the issues, including an incremental clustering phase, a sub-trajectory detecting phase and a cluster filtering phase. Experiments upon real-life data sets demonstrate the effectiveness and efficiency of the proposed framework.作者: 不發(fā)音 時間: 2025-3-22 23:12
Point-of-Interest Recommendations by Unifying Multiple Correlationsnify different information in a framework and learn the exact function by using gradient descent methods. The experimental results on real-world data sets show that our recommendations are more effective than baseline methods.作者: Guileless 時間: 2025-3-23 02:55
Point-of-Interest Recommendations by Unifying Multiple Correlationsnify different information in a framework and learn the exact function by using gradient descent methods. The experimental results on real-world data sets show that our recommendations are more effective than baseline methods.作者: 暫停,間歇 時間: 2025-3-23 09:21 作者: murmur 時間: 2025-3-23 11:39 作者: Mnemonics 時間: 2025-3-23 15:33
A Novel Chinese Text Mining Method for E-Commerce Review Spam Detectionuct fine-grained analysis to recognize the semantic orientation. We study the spammers’ behavior patterns and come up with four effective features to describe untruthful comments. We train classifier to classify reviews into spam or non-spam. Experiments are conducted to demonstrate the excellent performance of our algorithm.作者: 圍巾 時間: 2025-3-23 19:44
Conference proceedings 2016ewed and selected from 266 submissions. The focus of the conference is on following topics: data mining, spatial and temporal databases, recommender systems, graph data management, information retrieval, privacy and trust, query processing and optimization, social media, big data analytics, and distributed and cloud computing.作者: 繼而發(fā)生 時間: 2025-3-24 00:58
0302-9743 national Conference on Web-Age Information Management, WAIM 2016, held in Nanchang, China, in June 2016..The 80 full research papers presented together with 8 demonstrations were carefully reviewed and selected from 266 submissions. The focus of the conference is on following topics: data mining, sp作者: Encumber 時間: 2025-3-24 04:03
Effectively Updating High Utility Co-location Patterns in Evolving Spatial Databasesationships. The increasing of neighbors can affect the result of high utility co-location mining. This paper proposes an algorithm for efficiently updating high utility co-locations and evaluates the algorithm by experiments.作者: Aids209 時間: 2025-3-24 06:49
Effectively Updating High Utility Co-location Patterns in Evolving Spatial Databasesationships. The increasing of neighbors can affect the result of high utility co-location mining. This paper proposes an algorithm for efficiently updating high utility co-locations and evaluates the algorithm by experiments.作者: 弄皺 時間: 2025-3-24 11:57 作者: BINGE 時間: 2025-3-24 17:17 作者: Hippocampus 時間: 2025-3-24 22:10 作者: 宣傳 時間: 2025-3-25 01:06
More Efficient Algorithm for Mining Frequent Patterns with Multiple Minimum Supportsrithms, is that they rely on a single minimum support threshold to identify frequent patterns (FPs). As a solution, several algorithms have been proposed to mine FPs using multiple minimum supports. Nevertheless, a crucial problem is that these algorithms generally consume a large amount of memory a作者: recede 時間: 2025-3-25 05:05
Efficient Mining of Uncertain Data for High-Utility Itemsetsowever, uncertainty that are embedded in big data which collected from experimental measurements or noisy sensors in real-life applications. In this paper, an efficient algorithm, namely Mining Uncertain data for High-Utility Itemsets (MUHUI), is proposed to efficiently discover potential high-utili作者: Overstate 時間: 2025-3-25 08:57
Efficient Mining of Uncertain Data for High-Utility Itemsetsowever, uncertainty that are embedded in big data which collected from experimental measurements or noisy sensors in real-life applications. In this paper, an efficient algorithm, namely Mining Uncertain data for High-Utility Itemsets (MUHUI), is proposed to efficiently discover potential high-utili作者: promote 時間: 2025-3-25 13:27 作者: 四牛在彎曲 時間: 2025-3-25 18:49
An Improved HMM Model for Sensing Data Predicting in WSNnsolved problems for WSN. Predicting methods for data recovery by empirical treatment, mostly based on statistics has been studied exclusively. Machine learning models can greatly enhance the predicting performance. In this paper, an improved HMM is proposed for multi-step predicting of wireless sen作者: 空氣傳播 時間: 2025-3-25 23:12 作者: Barrister 時間: 2025-3-26 02:48
eXtreme Gradient Boosting for Identifying Individual Users Across Different Digital Devicesugh different electronic devices. Identifying individual users across different digital devices is now becoming a hot research topic. Methods based on name, email and other demographic information have received much attention. However, it is often difficult to obtain a complete set of information. I作者: 是他笨 時間: 2025-3-26 06:42 作者: 蛙鳴聲 時間: 2025-3-26 08:54
Two-Phase Mining for Frequent Closed Episodessode mining strategies have been suggested, which can be roughly classified into two classes: Apriori-based breadth-first algorithms and projection-based depth-first algorithms. As we know, both kinds of algorithms are level-wise pattern growth methods, so that they have higher computational overhea作者: archetype 時間: 2025-3-26 16:17
Effectively Updating High Utility Co-location Patterns in Evolving Spatial Databasesborhood. In spatial high utility co-location mining, we should consider the utility as a measure of interests, by considering the different value of individual instance that belongs to different feature. This paper presents a problem of updating high utility co-locations on evolving spatial database作者: pericardium 時間: 2025-3-26 17:50
Effectively Updating High Utility Co-location Patterns in Evolving Spatial Databasesborhood. In spatial high utility co-location mining, we should consider the utility as a measure of interests, by considering the different value of individual instance that belongs to different feature. This paper presents a problem of updating high utility co-locations on evolving spatial database作者: ineptitude 時間: 2025-3-26 23:51
Mining Top-, Distinguishing Sequential Patterns with Flexible Gap Constraintstein families. However, in previous studies on DSP mining, the gap constraints are very rigid – they are identical for all discovered patterns and at all positions in the discovered patterns, in addition to being predetermined. This paper considers a more flexible way to handle gap constraint, allow作者: 矛盾 時間: 2025-3-27 04:23 作者: atopic-rhinitis 時間: 2025-3-27 06:41
A Novel Chinese Text Mining Method for E-Commerce Review Spam Detectionovel Chinese text mining method to detect review spam automatically and efficiently. We correctly extract keywords in complicated review text and conduct fine-grained analysis to recognize the semantic orientation. We study the spammers’ behavior patterns and come up with four effective features to 作者: Bravura 時間: 2025-3-27 11:21
A Novel Chinese Text Mining Method for E-Commerce Review Spam Detectionovel Chinese text mining method to detect review spam automatically and efficiently. We correctly extract keywords in complicated review text and conduct fine-grained analysis to recognize the semantic orientation. We study the spammers’ behavior patterns and come up with four effective features to 作者: 詢問 時間: 2025-3-27 15:23 作者: Ancillary 時間: 2025-3-27 21:24
Retrieving Routes of Interest Over Road Networkst (i) its distance is less than a distance threshold and (ii) its relevance to the query keywords is maximized. ROI query is particularly helpful for tourists and city explorers. For example, a tourist may wish to find a route from a scenic spot to her hotel to cover many artware shops. It is challe作者: NICE 時間: 2025-3-28 01:36 作者: 安裝 時間: 2025-3-28 02:49 作者: condemn 時間: 2025-3-28 09:30 作者: disciplined 時間: 2025-3-28 11:52 作者: 假裝是你 時間: 2025-3-28 15:41
Ridesharing Recommendation: Whether and Where Should I Wait?r, we propose a recommendation framework to predict and recommend whether and where should the users wait to rideshare. In the framework, we utilize a large-scale GPS data set generated by over 7,000 taxis in a period of one month in Nanjing, China to model the arrival patterns of occupied taxis fro作者: 存在主義 時間: 2025-3-28 21:22 作者: 內(nèi)閣 時間: 2025-3-29 00:16
Keyword-aware Optimal Location Query in Road Network a client often wants to find a residence such that the sum of the distances between this residence and its nearest facilities is minimal, and meanwhile the residence should be on one of the client-selected road segments (representing where the client prefers to live). The facilities are categorized作者: GRAIN 時間: 2025-3-29 06:58 作者: 支柱 時間: 2025-3-29 11:06 作者: 繁重 時間: 2025-3-29 14:54
Point-of-Interest Recommendations by Unifying Multiple Correlations framework for location-aware recommender systems with the consideration of social influence, categorical influence and geographical influence for users’ preference. In the framework, we model the three types of information as functions following a power-law distribution, respectively. And then we u作者: 險代理人 時間: 2025-3-29 16:42
Top-, Team Recommendation in Spatial Crowdsourcingd Gmission, are getting popular. Most existing studies assume that spatial crowdsourced tasks are simple and trivial. However, many real crowdsourced tasks are complex and need to be collaboratively finished by a team of crowd workers with different skills. Therefore, an important issue of spatial c作者: 高貴領(lǐng)導(dǎo) 時間: 2025-3-29 22:00 作者: Pelvic-Floor 時間: 2025-3-30 01:27
Explicable Location Prediction Based on Preference Tensor Modelre personal services, the applications like location-aware advertising and route recommendation are interested not only in the predicted location but its explanation as well. In this paper, we investigate the problem of Explicable Location Prediction (ELP) from LBSN data, which is not easy due to th作者: 出生 時間: 2025-3-30 07:41
Explicable Location Prediction Based on Preference Tensor Modelre personal services, the applications like location-aware advertising and route recommendation are interested not only in the predicted location but its explanation as well. In this paper, we investigate the problem of Explicable Location Prediction (ELP) from LBSN data, which is not easy due to th作者: forthy 時間: 2025-3-30 11:06
Conference proceedings 2016Management, WAIM 2016, held in Nanchang, China, in June 2016..The 80 full research papers presented together with 8 demonstrations were carefully reviewed and selected from 266 submissions. The focus of the conference is on following topics: data mining, spatial and temporal databases, recommender s作者: 壁畫 時間: 2025-3-30 13:17 作者: BARK 時間: 2025-3-30 18:47 作者: gout109 時間: 2025-3-30 23:26 作者: 驚呼 時間: 2025-3-31 02:25 作者: comely 時間: 2025-3-31 07:32 作者: 變異 時間: 2025-3-31 09:46
Keyword-aware Optimal Location Query in Road Network and find the optimal locations by only inspecting the endpoints of the sub-intervals. We also propose an improved algorithm with keyword filtering and edge pruning strategies. Finally, we demonstrate the efficiency of our algorithms with extensive experiments on large-scale real datasets.作者: 不近人情 時間: 2025-3-31 14:57 作者: 織物 時間: 2025-3-31 21:34 作者: 對待 時間: 2025-3-31 23:51
More Efficient Algorithm for Mining Frequent Patterns with Multiple Minimum Supportshe ME-tree without generating candidates. Furthermore, an improved algorithms, named ., is also proposed based on the . concept, to further increase mining performance. Substantial experiments on real-life datasets show that the proposed approaches not only avoid the “rare item problem”, but also ef作者: assent 時間: 2025-4-1 04:03
More Efficient Algorithm for Mining Frequent Patterns with Multiple Minimum Supportshe ME-tree without generating candidates. Furthermore, an improved algorithms, named ., is also proposed based on the . concept, to further increase mining performance. Substantial experiments on real-life datasets show that the proposed approaches not only avoid the “rare item problem”, but also ef作者: 寒冷 時間: 2025-4-1 09:42
An Improved HMM Model for Sensing Data Predicting in WSNesults show that our proposed model can provide higher accuracy in sensing data predicting. This proposed model is promising in the fields of agriculture, industry and other domains, in which the sensing data usually contains various varying patterns.作者: 提煉 時間: 2025-4-1 10:56
An Improved HMM Model for Sensing Data Predicting in WSNesults show that our proposed model can provide higher accuracy in sensing data predicting. This proposed model is promising in the fields of agriculture, industry and other domains, in which the sensing data usually contains various varying patterns.作者: violate 時間: 2025-4-1 17:05 作者: 糾纏 時間: 2025-4-1 22:32 作者: Overstate 時間: 2025-4-1 23:56 作者: 修改 時間: 2025-4-2 06:25
Two-Phase Mining for Frequent Closed Episodesthe candidates with different prefixes to discover the final frequent closed episodes. The advantage of the suggested mining strategy is it can reduce mining time due to narrowing episode mapping range when doing closure judgment. Experiments on simulated and real datasets demonstrate that the sugge作者: 真實(shí)的你 時間: 2025-4-2 11:01 作者: inventory 時間: 2025-4-2 12:53
Mining Top-, Distinguishing Sequential Patterns with Flexible Gap Constraintsints. Our empirical study on real-world data sets demonstrates that GepDSP is effective and efficient, and DSPs with flexible gap constraints are more effective in capturing discriminating sequential patterns.作者: meditation 時間: 2025-4-2 18:00
Ridesharing Recommendation: Whether and Where Should I Wait?it by investigating the probabilities of possible destinations based on ridesharing requirements. Users are recommended to take a taxi directly if the potential to rideshare with others is not high enough. Experimental results show that the accuracy about whether ridesharing or not and the rideshari作者: 代替 時間: 2025-4-2 19:33 作者: consent 時間: 2025-4-3 01:04
Explicable Location Prediction Based on Preference Tensor Modelas the explanation of the prediction. To model the complicated motivations of human movement, we propose two motivation tensors, a social tensor and a personal tensor, to represent the social cause and the personal cause of human movement. From the motivation tensors, the motivation vector consistin作者: 大包裹 時間: 2025-4-3 07:39 作者: GONG 時間: 2025-4-3 11:58 作者: 機(jī)制 時間: 2025-4-3 14:51
Jerry Chun-Wei Lin,Wensheng Gan,Philippe Fournier-Viger,Tzung-Pei Hong,Vincent S. Tseng
