OpenRaiser/Intern-Atlas huggingface dataset:
Extraction and mining of an academic social network
Authors: Jie Tang, Jing Zhang, Limin Yao, Juan-Zi Li
Venue: WWW
Year: 2008

This paper addresses several key issues in extraction and mining of an academic social network: 1) extraction of a researcher social network from the existing Web; 2) integration of the publications from existing digital libraries; 3) expertise search on a given topic; and 4) association search between researchers. We developed a social network system, called ArnetMiner, based on proposed methods to the above problems. In total, 448,470 researcher profiles and 981,599 publications were extracted/integrated after the system having been in operation for two years. The paper describes the architecture and main features of the system. It also briefly presents the experimental results of the proposed methods.
A unified framework for name disambiguation
Authors: Jie Tang, Jing Zhang, Duo Zhang, Juanzi Li
Venue: WWW
Year: 2008

Name ambiguity problem has been a challenging issue for a long history. In this paper, we intend to make a thorough investigation of the whole problem. Specifically, we formalize the name disambiguation problem in a unified framework. The framework can incorporate both attribute and relationship into a probabilistic model. We explore a dynamic approach for automatically estimating the person number K and employ an adaptive distance measure to estimate the distance between objects. Experimental results show that our proposed framework can significantly outperform the baseline method.
Personalized view-based search and visualization as a means for deep/semantic web data access
Authors: Michal Tvarozek, Mária Bieliková
Venue: WWW
Year: 2008

Effective access to and navigation in information stored in deep Web ontological repositories or relational databases has yet to be realized due to issues with usability of user interfaces and the overall scope and complexity of information as well as the nature of exploratory user tasks. We propose the integration and adaptation of novel navigation and visualization approaches to faceted browsing such as visual depiction of facets and restrictions, visual navigation in (clusters of) search results and graph like exploration of individual search results' properties.
Why web 2.0 is good for learning and for research: principles and prototypes
Authors: Carsten Ullrich, Kerstin Borau, Heng Luo, Xiaohong Tan, Liping Shen, Ruimin Shen
Venue: WWW
Year: 2008

The term is used to describe applications that distinguish themselves from previous generations of software by a number of principles. Existing work shows that Web 2.0 applications can be successfully exploited for technology-enhance learning. However, in-depth analyses of the relationship between Web 2.0 technology on the one hand and teaching and learning on the other hand are still rare. In this article, we will analyze the technological principles of the Web 2.0 and describe their pedagogical implications on learning. We will furthermore show that Web 2.0 is not only well suited for learning but also for research on learning: the wealth of services that is available and their openness regarding API and data allow to assemble prototypes of technology-supported learning applications in amazingly small amount of time. These prototypes can be used to evaluate research hypotheses quickly. We will present two example prototypes and discuss the lessons we learned from building and using these prototypes.
Measuring extremal dependencies in web graphs
Authors: Yana Volkovich, Nelly Litvak, Bert Zwart
Venue: WWW
Year: 2008

We analyze dependencies in power law graph data (Web sample, Wikipedia sample and a preferential attachment graph) using statistical inference for multivariate regular variation. The well developed theory of regular variation is widely applied in extreme value theory, telecommunications and mathematical finance, and it provides a natural mathematical formalism for analyzing dependencies between variables with power laws. However, most of the proposed methods have never been used in the Web graph data mining. The present work fills this gap. The new insights this yields are striking: the three above-mentioned data sets are shown to have a totally different dependence structure between different graph parameters, such as in-degree and PageRank.
Cm-pmi: improved web-based association measure with contextual label matching
Authors: Xiaojun Wan
Venue: WWW
Year: 2008

WebPMI is a popular web-based association measure to evaluate the semantic similarity between two queries (i.e. words or entities) by leveraging search results returned by search engines. This paper proposes a novel measure named CM-PMI to evaluate query similarity at a finer granularity than WebPMI, under the assumption that a query is usually associated with more than one aspect and two queries are deemed semantically related if their associated aspect sets are highly consistent with each other. CM-PMI first extracts contextual labels from search results to represent the aspects of a query, and then uses the optimal matching method to assess the consistency between the aspects of two queries. Experimental results on the benchmark Miller Charles' dataset demonstrate the good effectiveness of the proposed CM-PMI measure. Moreover, we further fuse WebPMI and CM-PMI to obtain improved results.
Incremental web page template detection
Authors: Yu Wang, Binxing Fang, Xueqi Cheng, Li Guo, Hongbo Xu
Venue: WWW
Year: 2008

Most template detection methods process web pages in batches that a newly crawled page can not be processed until enough pages have been collected. This results in large storage consumption and a huge delay of data refreshing. In this paper, we present an incremental framework to detect templates in which a page is processed as soon as it has been crawled. In this framework, we don't need to cache any web page. Experiments show that our framework consumes less than 7% storage than traditional methods. And also the speed of data refreshing is accelerated because of the incremental manner.
Protecting web services from remote exploit code: a static analysis approach
Authors: Xinran Wang, Yoon-chan Jhi, Sencun Zhu, Peng Liu
Venue: WWW
Year: 2008

We propose STILL, a signature-free remote exploit binary code injection attack blocker to protect web servers and web applications. STILL is robust to almost all anti-signature, anti-static-analysis and anti-emulation obfuscation.
Service-oriented data denormalization for scalable web applications
Authors: Zhou Wei, Dejun Jiang, Guillaume Pierre, Chi-Hung Chi, Maarten van Steen
Venue: WWW
Year: 2008

Many techniques have been proposed to scale web applications. However, the data interdependencies between the database queries and transactions issued by the applications limit their efficiency. We claim that major scalability improvements can be gained by restructuring the web application data into multiple independent data services with exclusive access to their private data store. While this restructuring does not provide performance gains by itself, the implied simplification of each database workload allows a much more efficient use of classical techniques. We illustrate the data denormalization process on three benchmark applications: TPC-W, RUBiS and RUBBoS. We deploy the resulting service-oriented implementation of TPC-W across an 85-node cluster and show that restructuring its data can provide at least an order of magnitude improvement in the maximum sustainable throughput compared to master-slave database replication, while preserving strong consistency and transactional properties.
Utility-driven load shedding for xml stream processing
Authors: Mingzhu Wei, Elke A. Rundensteiner, Murali Mani
Venue: WWW
Year: 2008

Because of the high volume and unpredictable arrival rate, stream processing systems may not always be able to keep up with the input data streams - resulting in buffer overflow and uncontrolled loss of data. Load shedding, the prevalent strategy for solving this overflow problem, has so far only been considered for relational stream processing, but not for XML. Shedding applied to XML stream processing brings new opportunities and challenges due to complex nested nature of XML structures. In this paper, we tackle this unsolved XML shedding problem using a three-pronged approach. First, we develop an XQuery preference model that enables users to specify the relative importance of preserving different subpatterns in the XML result structure. This transforms shedding into the problem of rewriting the user query into shed queries that return approximate query answers with utility as measured by the given user preference model. Second, we develop a cost model to compare the performance of alternate shed queries. Third, we develop two shedding algorithms, OptShed and FastShed. OptShed guarantees to find an optimal solution however at the cost of exponential complexity. FastShed, as confirmed by our experiments, achieves a close-to-optimal result in a wide range of test cases. Finally we describe the in-automaton shedding mechanism for XQuery stream engines. The experiments show that our proposed utility-driven shedding solutions consistently achieve higher utility results compared to the existing relational shedding techniques.
International workshop on question answering on the web (QAWeb2008)
Authors: Liu Wenyin, Qing Li, Xuedong Huang
Venue: WWW
Year: 2008

A half-day single track workshop is designed to gather academic researchers and industrial practitioners at to share ideas and knowledge of know-how, and to discuss all relevant issues including the business models, enabling technologies, and killer applications, of Web-based question answering (QA), especially, the user-interactive QA services and applications. The workshop program consists of two sessions, one for academic papers, and the other for industrial practice papers. Each session consists of a leading talk, followed by three short presentations. Sufficient time is allocated for brainstorming discussions in each session.
Keyword extraction for contextual advertisement
Authors: Xiaoyuan Wu, Alvaro Bolivar
Venue: WWW
Year: 2008

As the largest online marketplace, eBay strives to promote its inventory throughout the Web via different types of online advertisement. Contextually relevant links to eBay assets on third party sites is one example of such advertisement avenues. Keyword extraction is the task at the core of any contextual advertisement system. In this paper, we explore a machine learning approach to this problem. The proposed solution uses linear and logistic regression models learnt from human labeled data, combined with document, text and eBay specific features. In addition, we propose a solution to identify the prevalent category of eBay items in order to solve the problem of keyword ambiguity.
Social and semantics analysis via non-negative matrix factorization
Authors: Zhi-Li Wu, Chi-Wa Cheng, Chun-hung Li
Venue: WWW
Year: 2008

Social media such as Web forum often have dense interactions between user and content where network models are often appropriate for analysis. Joint non-negative matrix factorization model of participation and content data can be viewed as a bipartite graph model between users and media and is proposed for analysis social media. The factorizations allow simultaneous automatic discovery of leaders and sub-communities in the Web forum as well as the core latent topics in the forum. Results on topic detection of Web forums and cluster analysis show that social features are highly effective for forum analysis.
Making BPEL flexible: adapting in the context of coordination constraints using WS-BPEL
Authors: Yunzhou Wu, Prashant Doshi
Venue: WWW
Year: 2008

Although WS-BPEL is emerging as the prominent language for modeling executable business processes, its support for designing flexible processes is limited.
System II: a hypergraph based native rdf repository
Authors: Gang Wu, Juan-Zi Li, Kehong Wang
Venue: WWW
Year: 2008

To manage the increasing amount of RDF data, an RDF repository should provide not only necessary scalability and efficiency, but also sufficient inference capabilities. In this paper, we propose a native RDF repository, System, to pursue a better tradeoff among the above requirements. System takes the hypergraph representation for RDF as the data model for its persistent storage, which effectively avoids the costs of data model transformation when accessing RDF data. In addition, a set of efficient semantic query processing techniques are designed. The results of performance evaluation on the LUBM benchmark show that System has a better combined metric value than the other comparable systems.
Personalized multimedia web summarizer for tourist
Authors: Xiao Wu, Jintao Li, Yongdong Zhang, Sheng Tang, Shi-Yong Neo
Venue: WWW
Year: 2008

In this paper, we highlight the use of multimedia technology in generating intrinsic summaries of tourism related information. The system utilizes an automated process to gather, filter and classify information on various tourist spots on the Web. The end result present to the user is a personalized multimedia summary generated with respect to users queries filled with text, image, video and real-time news made retrievable for mobile devices. Preliminary experiments demonstrate the superiority of our presentation scheme to traditional methods.
Efficient evaluation of generalized path pattern queries on XML data
Authors: Xiaoying Wu, Stefanos Souldatos, Dimitri Theodoratos, Theodore Dalamagas, Timos K. Sellis
Venue: WWW
Year: 2008

Finding the occurrences of structural patterns in XML data is a key operation in XML query processing. Existing algorithms for this operation focus almost exclusively on path-patterns or tree-patterns. Requirements in flexible querying of XML data have motivated recently the introduction of query languages that allow a partial specification of path-patterns in a query. In this paper, we focus on the efficient evaluation of partial path queries, a generalization of path pattern queries. Our approach explicitly deals with repeated labels (that is, multiple occurrences of the same label in a query).
An efficient two-phase service discovery mechanism
Authors: ShuiGuang Deng, Zhaohui Wu, Jian Wu, Ying Li
Venue: WWW
Year: 2008

We bring forward a two-phase semantic service discovery mechanism which supports both the operation matchmaking and operation-composition matchmaking. A serial of experiments on a service management framework show that the mechanism gains better performance on both discovery recall rate and precision than a traditional matchmaker.
Information retrieval and knowledge discovery on the semantic web of traditional chinese medicine
Authors: Zhaohui Wu, Tong Yu, Huajun Chen, Xiaohong Jiang, Yi Feng, Yuxin Mao, Heng Wang, Jingming Tang, Chunying Zhou
Venue: WWW
Year: 2008

We conduct the first systematical adoption of the Semantic Web solution in the integration, management, and utilization of TCM information and knowledge resources. As the results, the largest TCM Semantic Web ontology is engineered as the uniform knowledge representation mechanism; the ontology-based query and search engine is deployed, mapping legacy and heterogeneous relational databases to the Semantic Web layer for query and search across database boundaries; the first global herb-drug interaction network is mapped through semantic integration, and the semantic graph mining methodology is implemented for discovering and interpreting interesting patterns from this network. The platform and underlying methodology are proved effective in TCM-related drug usage, discovery, and safety analysis.
Rogue access point detection using segmental TCP jitter
Authors: Gaogang Xie, Tingting He, Guangxing Zhang
Venue: WWW
Year: 2008

Rogue Access Points (RAPs) pose serious security threats to local networks. An analytic model of prior probability distribution of Segmental TCP Jitter (STJ) is deduced from the mechanism of IEEE 802.11 MAC Distributed Coordinated Function (DCF) and used to differentiate the types of wire and WLAN connections which is the crucial step for RAPs detecting. STJ as the detecting metric can reflect more the characteristic of 802.11 MAC than ACK-Pair since it can eliminate the delay caused by packet transmission. The experiment on an operated network shows the average detection ratio of the algorithm with STJ is more than 92.8% and the average detection time is less than 1s with improvement of 20% and 60% over the detecting approach of ACK-Pair respectively. Farther more no WLAN training trace is needed in the detecting algorithm.
A systematic approach for cell-phone worm containment
Authors: Liang Xie, Hui Song, Trent Jaeger, Sencun Zhu
Venue: WWW
Year: 2008

Cell phones are increasingly becoming attractive targets of various worms, which cause the leakage of user privacy, extra service charges and depletion of battery power. In this work, we study propagation of cell-phone worms, which exploit Multimedia Messaging Service (MMS) and/or Bluetooth for spreading. We then propose a systematic countermeasure against the worms. At the terminal level, we adopt Graphic Turing test and identity-based signature to block unauthorized messages from leaving compromised phones; at the network level, we propose a push-based automated patching scheme for cleansing compromised phones. Through experiments on phone devices and a wide variety of networks, we show that cellular systems taking advantage of our defense can achieve a low infection rate (e.g., less than 3% within 30 hours) even under severe attacks.
Efficiently querying rdf data in triple stores
Authors: Ying Yan, Chen Wang, Aoying Zhou, Weining Qian, Li Ma, Yue Pan
Venue: WWW
Year: 2008

Efficiently querying RDF [1] data is being an important factor in applying Semantic Web technologies to real-world applications. In this context, many efforts have been made to store and query RDF data in relational database using particular schemas. In this paper, we propose a new scheme to store, index, and query RDF data in triple stores. Graph feature of RDF data is taken into considerations which might help reduce the join costs on the vertical database structure. We would partition RDF triples into overlapped groups, store them in a triple table with one more column of group identity, and build up a signature tree to index them. Based on this infrastructure, a complex RDF query is decomposed into multiple pieces of sub-queries which could be easily filtered into some RDF groups using signature tree index, and finally is evaluated with a composed and optimized SQL with specific constraints. We compare the performance of our method with prior art on typical queries over a large scaled LUBM and UOBM benchmark data (more than 10 million triples)in [3]. For some extreme cases, they can promote3to4ordersofmagnitude.
Automatic web image selection with a probabilistic latent topic model
Authors: Keiji Yanai
Venue: WWW
Year: 2008

We propose a new method to select relevant images to the given keywords from images gathered from theWeb based on the Probabilistic Latent Semantic Analysis (PLSA) model which is a probabilistic latent topic model originally proposed for text document analysis. The experimental results shows that the results by the proposed method is almost equivalent to or outperforms the results by existing methods. In addition, it is proved that our method can select more various images compared to the existing SVM-based methods.
Lock-free consistency control for web 2.0 applications
Authors: Jiangming Yang, Haixun Wang, Ning Gu, Yiming Liu, Chunsong Wang, Qiwei Zhang
Venue: WWW
Year: 2008

Online collaboration and sharing is the central theme of many web-based services that create the so-called Web 2.0 phenomena. Using the Internet as a computing platform, many Web 2.0 applications set up mirror sites to provide large-scale availability and to achieve load balance. However, in the age of Web 2.0, where every user is also a writer and publisher, the deployment of mirror sites makes consistency maintenance a Web scale problem. Traditional concurrency control methods (e.g. two phase lock, serialization, etc.) are not up to the task for several reasons. First, large network latency between mirror sites will make two phase locking a throughput bottleneck. Second, locking will block a large portion of concurrent operations, which makes it impossible to provide large-scale availability. On the other hand, most Web 2.0 operations do not need strict serializability - it is not the intention of a user who is correcting a typo in a shared document to block another who is adding a comment, as long as consistency can still be achieved. Thus, in order to enable maximal online collaboration and sharing, we need a lock-free mechanism that can maintain consistency among mirror sites on the Web. In this paper, we propose a flexible and efficient method to achieve consistency maintenance in the Web 2.0 world. Our experiments show its good performance improvement compared with existing methods based on distributed lock.
Towards a global schema for web entities
Authors: Conglei Yao, Yongjian Yu, Sicong Shou, Xiaoming Li
Venue: WWW
Year: 2008

Popular entities often have thousands of instances on the Web. In this paper, we focus on the case where they are presented in table-like format, namely appearing with their attribute names. It is observed that, on one hand, for the same entity, different web pages often incorporate different attributes; on the other, for the same attribute, different web pages often use different attribute names (labels). Therefore, it is imaginably difficult to produce a global attribute schema for all the web entities of a given entity type based on their web instances, although the global attribute schema is usually highly desired in web entity instances integration and web object extraction. To this end, we propose a novel framework of automatically learning a global attribute schema for all web entities of one specific entity type. Under this framework, an iterative instances extraction procedure is first employed to extract sufficient web entity instances to discover enough attribute labels. Next, based on the labels, entity instances, and related web pages, a maximum entropy-based schema discovery approach is adopted to learn the global attribute schema for the target entity type. Experimental results on the Chinese Web achieve weighted average Fscores of 0.7122 and 0.7123 on two global attribute schemas for person-type and movie-type web entities, respectively. These results show that our framework is general, efficient and effective.