OpenRaiser/Intern-Atlas huggingface dataset:
User-centric content freshness metrics for search engines
Authors: Ali Dasdan, Xinh Huynh
Venue: WWW
Year: 2009

In order to return relevant search results, a search engine must keep its local repository synchronized to the Web, but it is usually impossible to attain perfect freshness. Hence, it is vital for a production search engine continually to monitor and improve repository freshness. Most previous freshness metrics, formulated in the context of developing better synchronization policies, focused on the web crawler while ignoring other parts of a search engine. But, the freshness of documents in a web crawler does not necessarily translate directly into the freshness of search results as seen by users. We propose metrics for measuring freshness from a user’s perspective, which take into account the latency between when documents are crawled and when they are viewed by users, as well as the variation in user click and view frequency among different documents. We also describe a practical implementation of these metrics that were used in a production search engine.
SGPS: a semantic scheme for web service similarity
Authors: Sourish Dasgupta, Satish Bhat, Yugyung Lee
Venue: WWW
Year: 2009

Today's Web becomes a platform for services to be dynamically interconnected to produce a desired outcome. It is important to formalize the semantics of the contextual elements of web services. In this paper, we propose a novel technique called Semantic Genome Propagation Scheme (SGPS) for measuring similarity between semantic concepts. We show how SGPS is used to compute a multi-dimensional similarity between two services. We evaluate the SGPS similarity measurement in terms of the similarity performance and scalability.
Automated synthesis of composite services with correctness guarantee
Authors: Ting Deng, Jinpeng Huai, Xianxian Li, Zongxia Du, Huipeng Guo
Venue: WWW
Year: 2009

In this paper, we propose a novel approach for composing existing web services to satisfy the correctness constraints to the design, including freeness of deadlock and unspecified reception, and temporal constraints in Computation Tree Logic formula. An automated synthesis algorithm based on learning algorithm is introduced, which guarantees that the composite service is the most general way of coordinating services so that the correctness is ensured. We have implemented a prototype system evaluating the effectiveness and efficiency of our synthesis approach through an experimental study.
Unsupervised query categorization using automatically-built concept graphs
Authors: Eustache Diemert, Gilles Vandelle
Venue: WWW
Year: 2009

Automatic categorization of user queries is an important component of general purpose (Web) search engines, particularly for triggering rich, query-specific content and sponsored links. We propose an unsupervised learning scheme that reduces dramatically the cost of setting up and maintaining such a categorizer, while retaining good categorization power. The model is stored as a graph of concepts where graph edges represent the cross-reference between the concepts. Concepts and relations are extracted from query logs by an offline Web mining process, which uses a search engine as a powerful summarizer for building a concept graph. Empirical evaluation indicates that the system compares favorably on publicly available data sets (such as KDD Cup 2005) as well as on portions of the current query stream of Yahoo! Search, where it is already changing the experience of millions of Web search users.
Using graphics processors for high performance IR query processing
Authors: Shuai Ding, Jinru He, Hao Yan, Torsten Suel
Venue: WWW
Year: 2009

Web search engines are facing formidable performance challenges due to data sizes and query loads. The major engines have to process tens of thousands of queries per second over tens of billions of documents. To deal with this heavy workload, such engines employ massively parallel systems consisting of thousands of machines. The significant cost of operating these systems has motivated a lot of recent research into more efficient query processing mechanisms. We investigate a new way to build such high performance IR systems using graphical processing units (GPUs). GPUs were originally designed to accelerate computer graphics applications through massive on-chip parallelism. Recently a number of researchers have studied how to use GPUs for other problem domains such as databases and scientific computing. Our contribution here is to design a basic system architecture for GPU-based high-performance IR, to develop suitable algorithms for subtasks such as inverted list compression, list intersection, and top-$k$ scoring, and to show how to achieve highly efficient query processing on GPU-based systems. Our experimental results for a prototype GPU-based system on $25.2$ million web pages indicate that significant gains in query processing performance can be obtained.
An experimental study of large-scale mobile social network
Authors: Zhengbin Dong, Guo-Jie Song, Kun-Qing Xie, Jingyao Wang
Venue: WWW
Year: 2009

Mobile social network is a typical social network where one or more individuals of similar interests or commonalities, conversing and connecting with one another using the mobile phone. Our works in this paper focus on the experimental study for this kind of social network with the support of large-scale real mobile call data. The main contributions can be summarized as three-fold: firstly, a large-scale real mobile phone call log of one city has been extracted from a mobile phone carrier in China to construct mobile social network; secondly, common features of traditional social networks, such as power law distribution and small diameter etc, have been experimented, with which we confirm that the mobile social network is a typical scale-free network and has small-world phenomenon; lastly, different from traditional analytical methods, important properties of the actors, such as gender and age, have been introduced into our experiments with some interesting findings about human behavior, for example, the middle-age people are more active than the young and old people, and the female is unusual more active than the male while in the old age.
Signaling emotion in tagclouds
Authors: Takeharu Eda, Toshio Uchiyama, Tadasu Uchiyama, Masatoshi Yoshikawa
Venue: WWW
Year: 2009

In order to create more attractive tagclouds that get people interested in tagged content, we propose a simple but novel tagcloud where font size is determined by tag's entropy value, not the popularity to its content. Our method raises users' emotional interest in the content by emphasizing more emotional tags. Our initial experiments show that emotional tagclouds attract more attention than normal tagclouds at first look; thus they will enhance the role of tagcloud as a social signaller.
Network-aware forward caching
Authors: Jeffrey Erman, Alexandre Gerber, Mohammad Taghi Hajiaghayi, Dan Pei, Oliver Spatscheck
Venue: WWW
Year: 2009

This paper proposes and evaluates a Network Aware Forward Caching approach for determining the optimal deployment strategy of forward caches to a network. A key advantage of this approach is that we can reduce the network costs associated with forward caching to maximize the benefit obtained from their deployment. We show in our simulation that a 37% increase to net benefits could be achieved over the standard method of full cache deployment to cache all POPs traffic. In addition, we show that this maximal point occurs when only 68% of the total traffic is cached.
XQuery in the browser
Authors: Ghislain Fourny, Markus Pilman, Daniela Florescu, Donald Kossmann, Tim Kraska, Darin McBeath
Venue: WWW
Year: 2009

Since the invention of the Web, the browser has become more and more powerful. By now, it is a programming and execution environment in itself. The predominant language to program applications in the browser today is JavaScript. With browsers becoming more powerful, JavaScript has been extended and new layers have been added (e.g., DOM-Support and XPath). Today, JavaScript is very successful and applications and GUI features implemented in the browser have become increasingly complex. The purpose of this paper is to improve the programmability of Web browsers by enabling the execution of XQuery programs in the browser. Although it has the potential to ideally replace JavaScript, it is possible to run it in addition to JavaScript for more flexibility. Furthermore, it allows instant code migration from the server to the client and vice-versa. This enables a significant simplification of the technology stack. The intuition is that programming the browser involves mostly XML (i.e., DOM) navigation and manipulation, and the XQuery family of W3C standards were designed exactly for that purpose. The paper proposes extensions to XQuery for Web browsers and gives a number of examples that demonstrate the usefulness of XQuery for the development of AJAX-style applications. Furthermore, the paper presents the design of an XQuery plug-in for Microsoft's Internet Explorer. The paper also gives examples of applications which were developed with the help of this plug-in.
A flexible dialogue system for enhancing web usability
Authors: Marta Gatius, Meritxell González
Venue: WWW
Year: 2009

In this paper, we study how the performance and usability of web dialogue systems could be enhanced by using an appropriate representation of the different types of knowledge involved in communication: general dialogue mechanisms, specific domain-restricted linguistic and conceptual knowledge and information on how well the communication process is doing. We describe the experiments carried out to analyze how to improve this knowledge representation in the web dialogue system we developed.
Link based small sample learning for web spam detection
Authors: Guanggang Geng, Qiudan Li, Xinchang Zhang
Venue: WWW
Year: 2009

Robust statistical learning based web spam detection system often requires large amounts of labeled training data. However, labeled samples are more difficult, expensive and time consuming to obtain than unlabeled ones. This paper proposed link based semi-supervised learning algorithms to boost the performance of a classifier, which integrates the traditional Self-training with the topological dependency based link learning. The experiments with a few labeled samples on standard WEBSPAM-UK2006 benchmark showed that the algorithms are effective.
Discovering user profiles
Authors: Riddhiman Ghosh, Mohamed Dekhil
Venue: WWW
Year: 2009

In this paper we describe techniques for the discovery and construction of user profiles. Leveraging from the emergent data web, our system addresses the problem of sparseness of user profile information currently faced by both asserted and inferred profile systems. A profile mediator, that dynamically builds the most suitable user profile for a particular service or interaction in real-time, is employed in our prototype implementation.
Hybrid keyword search auctions
Authors: Ashish Goel, Kamesh Munagala
Venue: WWW
Year: 2009

Search auctions have become a dominant source of revenue generation on the Internet. Such auctions have typically used per-click bidding and pricing. We propose the use of hybrid auctions where an advertiser can make a per-impression as well as a per-click bid, and the auctioneer then chooses one of the two as the pricing mechanism. We assume that the advertiser and the auctioneer both have separate beliefs (called priors) on the click-probability of an advertisement. We first prove that the hybrid auction is truthful, assuming that the advertisers are risk-neutral. We then show that this auction is superior to the existing per-click auction in multiple ways: We show that risk-seeking advertisers will choose only a per-impression bid whereas risk-averse advertisers will choose only a per-click bid, and argue that both kind of advertisers arise naturally. Hence, the ability to bid in a hybrid fashion is important to account for the risk characteristics of the advertisers. For obscure keywords, the auctioneer is unlikely to have a very sharp prior on the click-probabilities. In such situations, we show that having the extra information from the advertisers in the form of a per-impression bid can result in significantly higher revenue. An advertiser who believes that its click-probability is much higher than the auctioneer's estimate can use per-impression bids to correct the auctioneer's prior without incurring any extra cost. The hybrid auction can allow the advertiser and auctioneer to implement complex dynamic programming strategies to deal with the uncertainty in the click-probability using the same basic auction. The per-click and per-impression bidding schemes can only be used to implement two extreme cases of these strategies. As Internet commerce matures, we need more sophisticated pricing models to exploit all the information held by each of the participants. We believe that hybrid auctions could be an important step in this direction. The hybrid auction easily extends to multiple slots, and is also applicable to scenarios where the hybrid bidding is per-impression and per-action (i.e. CPM and CPA), or per-click and per-action (i.e. CPC and CPA).
Social search in "Small-World" experiments
Authors: Sharad Goel, Roby Muhamad, Duncan J. Watts
Venue: WWW
Year: 2009

The "algorithmic small-world hypothesis" states that not only are pairs of individuals in a large social network connected by short paths, but that ordinary individuals can find these paths. Although theoretically plausible, empirical evidence for the hypothesis is limited, as most chains in "small-world" experiments fail to complete, thereby biasing estimates of "true" chain lengths. Using data from two recent small-world experiments, comprising a total of 162,328 message chains, and directed at one of 30 "targets" spread across 19 countries, we model heterogeneity in chain attrition rates as a function of individual attributes. We then introduce a rigorous way of estimating true chain lengths that is provably unbiased, and can account for empirically-observed variation in attrition rates. Our findings provide mixed support for the algorithmic hypothesis. On the one hand, it appears that roughly half of all chains can be completed in 6-7 steps--thus supporting the "six degrees of separation" assertion--but on the other hand, estimates of the mean are much longer, suggesting that for at least some of the population, the world is not "small" in the algorithmic sense. We conclude that search distances in social networks are fundamentally different from topological distances, for which the mean and median of the shortest path lengths between nodes tend to be similar.
What's up CAPTCHA?: a CAPTCHA based on image orientation
Authors: Rich Gossweiler, Maryam Kamvar, Shumeet Baluja
Venue: WWW
Year: 2009

We present a new CAPTCHA which is based on identifying an image's upright orientation. This task requires analysis of the often complex contents of an image, a task which humans usually perform well and machines generally do not. Given a large repository of images, such as those from a web search result, we use a suite of automated orientation detectors to prune those images that can be automatically set upright easily. We then apply a social feedback mechanism to verify that the remaining images have a human-recognizable upright orientation. The main advantages of our CAPTCHA technique over the traditional text recognition techniques are that it is language-independent, does not require text-entry (e.g. for a mobile device), and employs another domain for CAPTCHA generation beyond character obfuscation. This CAPTCHA lends itself to rapid implementation and has an almost limitless supply of images. We conducted extensive experiments to measure the viability of this technique.
Estimating web site readability using content extraction
Authors: Thomas Gottron, Ludger Martin
Venue: WWW
Year: 2009

Nowadays, information is primarily searched on the WWW. From a user perspective, the readability is an important criterion for measuring the accessibility and thereby the quality of an information. We show that modern content extraction algorithms help to estimate the readability of a web document quite accurate.
A class-feature-centroid classifier for text categorization
Authors: Hu Guan, Jingyu Zhou, Minyi Guo
Venue: WWW
Year: 2009

Automated text categorization is an important technique for many web applications, such as document indexing, document filtering, and cataloging web resources. Many different approaches have been proposed for the automated text categorization problem. Among them, centroid-based approaches have the advantages of short training time and testing time due to its computational efficiency. As a result, centroid-based classifiers have been widely used in many web applications. However, the accuracy of centroid-based classifiers is inferior to SVM, mainly because centroids found during construction are far from perfect locations.
Click chain model in web search
Authors: Fan Guo, Chao Liu, Anitha Kannan, Tom Minka, Michael J. Taylor, Yi Min Wang, Christos Faloutsos
Venue: WWW
Year: 2009

Given a terabyte click log, can we build an efficient and effective click model? It is commonly believed that web search click logs are a gold mine for search business, because they reflect users' preference over web documents presented by the search engine. Click models provide a principled approach to inferring user-perceived relevance of web documents, which can be leveraged in numerous applications in search businesses. Due to the huge volume of click data, scalability is a must.We present the click chain model (CCM), which is based on a solid, Bayesian framework. It is both scalable and incremental, perfectly meeting the computational challenges imposed by the voluminous click logs that constantly grow. We conduct an extensive experimental study on a data set containing 8.8 million query sessions obtained in July 2008 from a commercial search engine. CCM consistently outperforms two state-of-the-art competitors in a number of metrics, with over 9.7% better log-likelihood, over 6.2% better click perplexity and much more robust (up to 30%) prediction of the first and the last clicked position.
Predicting click through rate for job listings
Authors: Manish S. Gupta
Venue: WWW
Year: 2009

Click Through Rate (CTR) is an important metric for ad systems, job portals, recommendation systems. CTR impacts publisher's revenue, advertiser's bid amounts in "pay for performance" business models. We learn regression models using features of the job, optional click history of job, features of "related" jobs. We show that our models predict CTR much better than predicting avg. CTR for all job listings, even in absence of the click history for the job listing.
Web 2.0: blind to an accessible new world
Authors: Joshua M. Hailpern, Loretta Guarino Reid, Richard Boardman, Srinivas Annam
Venue: WWW
Year: 2009

With the advent of Web 2.0 technologies, websites have evolved from static pages to dynamic, interactive Web-based applications with the ability to replicate common desktop functionality. However, for blind and visually impaired individuals who rely upon screen readers, Web 2.0 applications force them to adapt to an inaccessible use model. Many technologies, including WAI-ARIA, AJAX, and improved screen reader support, are rapidly evolving to improve this situation. However, simply combining them does not solve the problems of screen reader users. The main contributions of this paper are two models of interaction for screen reader users, for both traditional websites and Web 2.0 applications. Further contributions are a discussion of accessibility difficulties screen reader users encounter when interacting with Web 2.0 applications, a user workflow design model for improving Web 2.0 accessibility, and a set of design requirements for developers to ease the user's burden and increase accessibility. These models, accessibility difficulties, and design implications are based directly on responses and lessons learned from usability research focusing on Web 2.0 usage and screen reader users. Without the conscious effort of Web engineers and designers, most blind and visually impaired users will shy away from using new Web 2.0 technology in favor of desktop based applications.
Is there anything worth finding on the semantic web?
Authors: Harry Halpin
Venue: WWW
Year: 2009

There has recently been an upsurge of interest in the possibilities of combining structured data and ad-hoc information retrieval from traditional hypertext. In this experiment, we run queries extracted from a query log of a major search engine against the Semantic Web to discover if the Semantic Web has anything of interest to the average user. We show that there is indeed much information on the Semantic Web that could be relevant for many queries for people, places and even abstract concepts, although they are overwhelmingly clustered around a Semantic Web-enabled export of Wikipedia known as DBPedia.
A declarative framework for semantic link discovery over relational data
Authors: Oktie Hassanzadeh, Lipyeow Lim, Anastasios Kementsietsidis, Min Wang
Venue: WWW
Year: 2009

In this paper, we present a framework for online discovery of semantic links from relational data. Our framework is based on declarative specification of the linkage requirements by the user, that allows matching data items in many real-world scenarios. These requirements are translated to queries that can run over the relational data source, potentially using the semantic knowledge to enhance the accuracy of link discovery. Our framework lets data publishers to easily find and publish high-quality links to other data sources, and therefore could significantly enhance the value of the data in the next generation of web.
Threshold selection for web-page classification with highly skewed class distribution
Authors: Xiaofeng He, Lei Duan, Yiping Zhou, Byron Dom
Venue: WWW
Year: 2009

We propose a novel cost-efficient approach to threshold selection for binary web-page classification problems with imbalanced class distributions. In many binary-classification tasks the distribution of classes is highly skewed. In such problems, using uniform random sampling in constructing sample sets for threshold setting requires large sample sizes in order to include a statistically sufficient number of examples of the minority class. On the other hand, manually labeling examples is expensive and budgetary considerations require that the size of sample sets be limited. These conflicting requirements make threshold selection a challenging problem. Our method of sample-set construction is a novel approach based on stratified sampling, in which manually labeled examples are expanded to reflect the true class distribution of the web-page population. Our experimental results show that using false positive rate as the criterion for threshold setting results in lower-variance threshold estimates than using other widely used accuracy measures such as F1 and precision.
Reliability analysis using weighted combinational models for web-based software
Authors: Chao-Jung Hsu, Chin-Yu Huang
Venue: WWW
Year: 2009

In the past, some researches suggested that engineers can use combined software reliability growth models (SRGMs) to obtain more accurate reliability prediction during testing. In this paper, three weighted combinational models, namely, equal, linear, and nonlinear weight, are proposed for reliability estimation of web-based software. We further investigate the estimation accuracy of using genetic algorithm to determine the weight assignment for the proposed models. Preliminary result shows that the linearly and nonlinearly weighted combinational models have better prediction capability than single SRGM and equally weighted combinational model for web-based software.