The World Wide Web Conference最新文献_第7页

Rethinking the Detection of Child Sexual Abuse Imagery on the Internet 对网络儿童性侵图像检测的再思考

The World Wide Web Conference Pub Date : 2019-05-13 DOI: 10.1145/3308558.3313482

Elie Bursztein, Einat Clarke, Michelle DeLaune, David M. Elifff, Nick Hsu, Lindsey Olson, John Shehan, Madhukar Thakur, Kurt Thomas, Travis Bright

引用次数: 60

Addressing Trust Bias for Unbiased Learning-to-Rank 解决信任偏见的无偏学习排序

The World Wide Web Conference Pub Date : 2019-05-13 DOI: 10.1145/3308558.3313697

Aman Agarwal, Xuanhui Wang, Cheng Li, Michael Bendersky, Marc Najork

引用次数: 74

A Family of Fuzzy Orthogonal Projection Models for Monolingual and Cross-lingual Hypernymy Prediction 一组用于单语和跨语夸张预测的模糊正交投影模型

The World Wide Web Conference Pub Date : 2019-05-13 DOI: 10.1145/3308558.3313439

Chengyu Wang, Yan Fan, Xiaofeng He, Aoying Zhou

{"title":"A Family of Fuzzy Orthogonal Projection Models for Monolingual and Cross-lingual Hypernymy Prediction","authors":"Chengyu Wang, Yan Fan, Xiaofeng He, Aoying Zhou","doi":"10.1145/3308558.3313439","DOIUrl":"https://doi.org/10.1145/3308558.3313439","url":null,"abstract":"Hypernymy is a semantic relation, expressing the “is-a” relation between a concept and its instances. Such relations are building blocks for large-scale taxonomies, ontologies and knowledge graphs. Recently, much progress has been made for hypernymy prediction in English using textual patterns and/or distributional representations. However, applying such techniques to other languages is challenging due to the high language dependency of these methods and the lack of large training datasets of lower-resourced languages. In this work, we present a family of fuzzy orthogonal projection models for both monolingual and cross-lingual hypernymy prediction. For the monolingual task, we propose a Multi-Wahba Projection (MWP) model to distinguish hypernymy vs. non-hypernymy relations based on word embeddings. This model establishes distributional fuzzy mappings from embeddings of a term to those of its hypernyms and non-hypernyms, which consider the complicated linguistic regularities of these relations. For cross-lingual hypernymy prediction, a Transfer MWP (TMWP) model is proposed to transfer the semantic knowledge from the source language to target languages based on neural word translation. Additionally, an Iterative Transfer MWP (ITMWP) model is built upon TMWP, which augments the training sets of target languages when target languages are lower-resourced with limited training data. Experiments show i) MWP outperforms previous methods over two hypernymy prediction tasks for English; and ii) TMWP and ITMWP are effective to predict hypernymy over seven non-English languages.","PeriodicalId":23013,"journal":{"name":"The World Wide Web Conference","volume":"158 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81560714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 15

ContraVis: Contrastive and Visual Topic Modeling for Comparing Document Collections 对比:比较文档集合的对比和可视化主题建模

The World Wide Web Conference Pub Date : 2019-05-13 DOI: 10.1145/3308558.3313617

T. Le, L. Akoglu

{"title":"ContraVis: Contrastive and Visual Topic Modeling for Comparing Document Collections","authors":"T. Le, L. Akoglu","doi":"10.1145/3308558.3313617","DOIUrl":"https://doi.org/10.1145/3308558.3313617","url":null,"abstract":"Given posts on 'abortion' and posts on 'religion' from a political forum, how can we find topics that are discriminative and those in common? In general, (1) how can we compare and contrast two or more different ('labeled') document collections? Moreover, (2) how can we visualize the data (in 2-d or 3-d) to best reflect the similarities and differences between the collections? We introduce (to the best of our knowledge) the first contrastive and visual topic model, called ContraVis, that jointly addresses both problems: (1) contrastive topic modeling, and (2) contrastive visualization. That is, ContraVis learns not only latent topics but also embeddings for the documents, topics and labels for visualization. ContraVis exhibits three key properties by design. It is (i) Contrastive: It enables comparative analysis of different document corpora by extracting latent discriminative and common topics across labeled documents; (ii) Visually-expressive: Different from numerous existing models, it also produces a visualization for all of the documents, labels, and the extracted topics, where proximity in the coordinate space is reflective of proximity in semantic space; (iii) Unified: It extracts topics and visual coordinates simultaneously under a joint model. Through extensive experiments on real-world datasets, we show ContraVis 's potential for providing visual contrastive analysis of multiple document collections. We show both qualitatively and quantitatively that ContraVis significantly outperforms both unsupervised and supervised state-of-the-art topic models in contrastive power, semantic coherence and visual effectiveness.","PeriodicalId":23013,"journal":{"name":"The World Wide Web Conference","volume":"27 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"81912831","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12

Self- and Cross-Excitation in Stack Exchange Question & Answer Communities 堆栈交换问答社区中的自激励和交叉激励

The World Wide Web Conference Pub Date : 2019-05-13 DOI: 10.1145/3308558.3313440

Tiago Santos, Simon Walk, Roman Kern, M. Strohmaier, D. Helic

引用次数: 7

NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorization 基于稀疏矩阵分解的大规模网络嵌入

The World Wide Web Conference Pub Date : 2019-05-13 DOI: 10.1145/3308558.3313446

J. Qiu, Yuxiao Dong, Hao Ma, Jun Yu Li, Chi Wang, Kuansan Wang, Jie Tang

{"title":"NetSMF: Large-Scale Network Embedding as Sparse Matrix Factorization","authors":"J. Qiu, Yuxiao Dong, Hao Ma, Jun Yu Li, Chi Wang, Kuansan Wang, Jie Tang","doi":"10.1145/3308558.3313446","DOIUrl":"https://doi.org/10.1145/3308558.3313446","url":null,"abstract":"We study the problem of large-scale network embedding, which aims to learn latent representations for network mining applications. Previous research shows that 1) popular network embedding benchmarks, such as DeepWalk, are in essence implicitly factorizing a matrix with a closed form, and 2) the explicit factorization of such matrix generates more powerful embeddings than existing methods. However, directly constructing and factorizing this matrix-which is dense-is prohibitively expensive in terms of both time and space, making it not scalable for large networks. In this work, we present the algorithm of large-scale network embedding as sparse matrix factorization (NetSMF). NetSMF leverages theories from spectral sparsification to efficiently sparsify the aforementioned dense matrix, enabling significantly improved efficiency in embedding learning. The sparsified matrix is spectrally close to the original dense one with a theoretically bounded approximation error, which helps maintain the representation power of the learned embeddings. We conduct experiments on networks of various scales and types. Results show that among both popular benchmarks and factorization based methods, NetSMF is the only method that achieves both high efficiency and effectiveness. We show that NetSMF requires only 24 hours to generate effective embeddings for a large-scale academic collaboration network with tens of millions of nodes, while it would cost DeepWalk months and is computationally infeasible for the dense matrix factorization solution. The source code of NetSMF is publicly available1.","PeriodicalId":23013,"journal":{"name":"The World Wide Web Conference","volume":"8 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86204512","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 143

MARINE: Multi-relational Network Embeddings with Relational Proximity and Node Attributes 基于关系接近和节点属性的多关系网络嵌入

The World Wide Web Conference Pub Date : 2019-05-13 DOI: 10.1145/3308558.3313715

Ming-Han Feng, Chin-Chi Hsu, Cheng-te Li, Mi-Yen Yeh, Shou-de Lin

引用次数: 21

Review Response Generation in E-Commerce Platforms with External Product Information 具有外部产品信息的电子商务平台的评审响应生成

The World Wide Web Conference Pub Date : 2019-05-13 DOI: 10.1145/3308558.3313581

Lujun Zhao, Kaisong Song, Changlong Sun, Qi Zhang, Xuanjing Huang, Xiaozhong Liu

{"title":"Review Response Generation in E-Commerce Platforms with External Product Information","authors":"Lujun Zhao, Kaisong Song, Changlong Sun, Qi Zhang, Xuanjing Huang, Xiaozhong Liu","doi":"10.1145/3308558.3313581","DOIUrl":"https://doi.org/10.1145/3308558.3313581","url":null,"abstract":"''User reviews” are becoming an essential component of e-commerce. When buyers write a negative or doubting review, ideally, the sellers need to quickly give a response to minimize the potential impact. When the number of reviews is growing at a frightening speed, there is an urgent need to build a response writing assistant for customer service providers. In order to generate high-quality responses, the algorithm needs to consume and understand the information from both the original review and the target product. The classical sequence-to-sequence (Seq2Seq) methods can hardly satisfy this requirement. In this study, we propose a novel deep neural network model based on the Seq2Seq framework for the review response generation task in e-commerce platforms, which can incorporate product information by a gated multi-source attention mechanism and a copy mechanism. Moreover, we employ a reinforcement learning technique to reduce the exposure bias problem. To evaluate the proposed model, we constructed a large-scale dataset from a popular e-commerce website, which contains product information. Empirical studies on both automatic evaluation metrics and human annotations show that the proposed model can generate informative and diverse responses, significantly outperforming state-of-the-art text generation models.","PeriodicalId":23013,"journal":{"name":"The World Wide Web Conference","volume":"3 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78812517","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 16

Sensitivity Analysis of Centralities on Unweighted Networks 非加权网络中心性的敏感性分析

The World Wide Web Conference Pub Date : 2019-05-13 DOI: 10.1145/3308558.3313422

Shogo Murai, Yuichi Yoshida

{"title":"Sensitivity Analysis of Centralities on Unweighted Networks","authors":"Shogo Murai, Yuichi Yoshida","doi":"10.1145/3308558.3313422","DOIUrl":"https://doi.org/10.1145/3308558.3313422","url":null,"abstract":"Revealing important vertices is a fundamental task in network analysis. As such, many indicators have been proposed for doing so, which are collectively called centralities. However, the abundance of studies on centralities blurs their differences. In this work, we compare centralities based on their sensivitity to modifications in the graph. Specifically, we introduce a quantitative measure called (average-case) edge sensitivity, which measures how much the centrality value of a uniformly chosen vertex (or an edge) changes when we remove a uniformly chosen edge. Edge sensitivity is applicable to unweighted graphs, regarding which, to our knowledge, there has been no theoretical analysis of the centralities. We conducted a theoretical analysis of the edge sensitivities of six major centralities: the closeness centrality, harmonic centrality, betweenness centrality, endpoint betweenness centrality, PageRank, and spanning tree centrality. Our experimental results on synthetic and real graphs confirm the tendency predicted by the theoretical analysis. We also discuss an extension of edge sensitivity to the setting that we remove a uniformly chosen set of edges of size k for an integer k = 1.","PeriodicalId":23013,"journal":{"name":"The World Wide Web Conference","volume":"11 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2019-05-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"78573560","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 13

Unnecessarily Identifiable: Quantifying the fingerprintability of browser extensions due to bloat 不必要的可识别性:由于膨胀而量化浏览器扩展的可识别性

The World Wide Web Conference Pub Date : 2019-05-13 DOI: 10.1145/3308558.3313458

Oleksii Starov, Pierre Laperdrix, A. Kapravelos, Nick Nikiforakis

引用次数: 28