OpenRaiser/Intern-Atlas huggingface dataset:
Dynamic and graphical web page breakpoints
Authors: John J. Barton, Jan Odvarko
Venue: WWW
Year: 2010

Breakpoints are perhaps the quintessential feature of a de-bugger: they allow a developer to stop time and study the program state. Breakpoints are typically specified by selecting a line of source code. For large, complex, web pages with multiple developers, the relevant source line for a given user interface problem may not be known to the developer. In this paper we describe the implementation of breakpoints in dynamically created source, and on error messages, network events, DOMmutation, DOMobject property changes, and CSS style rule updates. Adding these domain-specific breakpoints to a general-purpose debugger for Javascript allows the developer to initiate the debugging process via Web page abstractions rather than lower level source code views. The breakpoints are implemented in the open source Fire-bug project, version 1.5, for the Firefox Web browser.
Access: news and blog analysis for the social sciences
Authors: Mikhail Bautin, Charles B. Ward, Akshay Patil, Steven Skiena
Venue: WWW
Year: 2010

The social sciences strive to understand the political, social, and cultural world around us, but have been impaired by limited access to the quantitative data sources enjoyed by the hard sciences. Careful analysis of Web document streams holds enormous potential to solve longstanding problems in a variety of social science disciplines through massive data analysis. This paper introduces the TextMap Access system, which provides ready access to a wealth of interesting statistics on millions of people, places, and things across a number of interesting web corpora. Powered by a flexible and scalable distributed statistics computation framework using Hadoop, continually updated corpora include newspapers, blogs, patent records, legal documents, and scientific abstracts; well over a terabyte of raw text and growing daily. The Lydia Textmap Access system, available through http://www.textmap.com/access, provides instant access for students and scholars through a convenient web user-interface. We describe the architecture of the TextMap Access system, and its impact on current research in political science, sociology, and business/marketing.
The anatomy of an ad: structured indexing and retrieval for sponsored search
Authors: Michael Bendersky, Evgeniy Gabrilovich, Vanja Josifovski, Donald Metzler
Venue: WWW
Year: 2010

The core task of sponsored search is to retrieve relevant ads for the user's query. Ads can be retrieved either by exact match, when their bid term is identical to the query, or by advanced match, which indexes ads as documents and is similar to standard information retrieval (IR). Recently, there has been a great deal of research into developing advanced match ranking algorithms. However, no previous research has addressed the ad indexing problem. Unlike most traditional search problems, the ad corpus is defined hierarchically in terms of advertiser accounts, campaigns, and ad groups, which further consist of creatives and bid terms. This hierarchical structure makes indexing highly non-trivial, as naively indexing all possible displayable ads leads to a prohibitively large and ineffective index. We show that ad retrieval using such an index is not only slow, but its precision is suboptimal as well. We investigate various strategies for compact, hierarchy-aware indexing of sponsored search ads through adaptation of standard IR indexing techniques. We also propose a new ad retrieval method that yields more relevant ads by exploiting the structured nature of the ad corpus. Experiments carried out over a large ad test collection from a commercial search engine show that our proposed methods are highly effective and efficient compared to more standard indexing and retrieval approaches.
Sync kit: a persistent client-side database caching toolkit for data intensive websites
Authors: Edward Benson, Adam Marcus 0002, David R. Karger, Samuel Madden 0001
Venue: WWW
Year: 2010

We introduce a client-server toolkit called Sync Kit that demonstrates how client-side database storage can improve the performance of data intensive websites. Sync Kit is designed to make use of the embedded relational database defined in the upcoming HTML5 standard to offload some data storage and processing from a web server onto the web browsers to which it serves content. Our toolkit provides various strategies for synchronizing relational database tables between the browser and the web server, along with a client-side template library so that portions web applications may be executed client-side. Unlike prior work in this area, Sync Kit persists both templates and data in the browser across web sessions, increasing the number of concurrent connections a server can handle by up to a factor of four versus that of a traditional server-only web stack and a factor of three versus a recent template caching approach.
Privacy in dynamic social networks
Authors: Smriti Bhagat, Graham Cormode, Balachander Krishnamurthy, Divesh Srivastava
Venue: WWW
Year: 2010

Anonymization of social networks before they are published or shared has become an important research question. Recent work on anonymizing social networks has looked at privacy preserving techniques for publishing a single instance of the network. However, social networks evolve and a single instance is inadequate for analyzing the evolution of the social network or for performing any longitudinal data analysis. We study the problem of repeatedly publishing social network data as the network evolves, while preserving privacy of users. Publishing multiple instances of the same network independently has privacy risks, since stitching the information together may allow an adversary to identify users in the networks.
Finding algorithms in scientific articles
Authors: Sumit Bhatia, Prasenjit Mitra, C. Lee Giles
Venue: WWW
Year: 2010

Algorithms are an integral part of computer science literature. However, none of the current search engines offer specialized algorithm search facility. We describe a vertical search engine that identifies the algorithms present in documents and extracts and indexes the related metadata and textual description of the identified algorithms. This algorithm specific information is then utilized for algorithm ranking in response to user queries. Experimental results show the superiority of our system on other popular search engines.
Automated performance assessment for service-oriented middleware: a case study on BPEL engines
Authors: Domenico Bianculli, Walter Binder, Mauro Luigi Drago
Venue: WWW
Year: 2010

Middleware for Web service compositions, such as BPEL engines, provides the execution environment for services as well as additional functionalities, such as monitoring and self-tuning. Given its role in service provisioning, it is very important to assess the performance of middleware in the context of a SOA. This paper presents SOABench, a framework for the automatic generation and execution of testbeds for benchmarking middleware for composite Web services and for assessing the performance of existing SOA infrastructures. SOABench defines a testbed model characterized by the composite services to execute, the workload to generate, the deployment configuration to use, the performance metrics to gather, the data analyses to perform on them, and the reports to produce. We have validated SOABench by benchmarking the performance of different BPEL engines.
Exploiting information redundancy to wring out structured data from the web
Authors: Lorenzo Blanco, Mirko Bronzi, Valter Crescenzi, Paolo Merialdo, Paolo Papotti
Venue: WWW
Year: 2010

A large number of web sites publish pages containing structured information about recognizable concepts, but these data are only partially used by current applications. Although such information is spread across a myriad of sources, the web scale implies a relevant redundancy. We present a domain independent system that exploits the redundancy of information to automatically extract and integrate data from the Web. Our solution concentrates on sources that provide structured data about multiple instances from the same conceptual domain, e.g. financial data, product information. Our proposal is based on an original approach that exploits the mutual dependency between the data extraction and the data integration tasks. Experiments confirmed the quality and the feasibility of the approach.
Caching search engine results over incremental indices
Authors: Roi Blanco, Edward Bortnikov, Flavio Junqueira, Ronny Lempel, Luca Telloli, Hugo Zaragoza
Venue: WWW
Year: 2010

A Web search engine must update its index periodically to incorporate changes to the Web, and we argue in this work that index updates fundamentally impact the design of search engine result caches. Index updates lead to the problem of cache invalidation: invalidating cached entries of queries whose results have changed. To enable efficient invalidation of cached results, we propose a framework for developing invalidation predictors and some concrete predictors. Evaluation using Wikipedia documents and a query log from Yahoo! shows that selective invalidation of cached search results can lower the number of query re-evaluations by as much as 30% compared to a baseline time-to-live scheme, while returning results of similar freshness.
Visual structure-based web page clustering and retrieval
Authors: Paul Bohunsky, Wolfgang Gatterbauer
Venue: WWW
Year: 2010

Clustering and retrieval of web pages dominantly relies on analyzing either the content of individual web pages or the link structure between them. Some literature also suggests to use the structure of web pages, notably the structure of its DOM tree. However, little work considers the visual structure of web pages for clustering. In this paper (i) we motivate visual structure-based web page clustering and retrieval for a number of applications, (ii) we formalize a visual box model-based representation of web pages that supports new metrics of visual similarity, and (iii) we report on our current work on evaluating human perception of visual similarity of web pages and applying the learned visual similarity features to web page clustering and retrieval.
Hearsay: a new generation context-driven multi-modal assistive web browser
Authors: Yevgen Borodin, Faisal Ahmed 0001, Muhammad Asiful Islam, Yury Puzis, Valentyn Melnyk, Song Feng 0002, I. V. Ramakrishnan, Glenn Dausch
Venue: WWW
Year: 2010

This demo will present HearSay, a multi-modal non-visual web browser, which aims to bridge the growing Web Accessibility divide between individuals with visual impairments and their sighted counterparts, and to facilitate full participation of blind individuals in the growing Web-based society.
Liquid query: multi-domain exploratory search on the web
Authors: Alessandro Bozzon, Marco Brambilla 0001, Stefano Ceri, Piero Fraternali
Venue: WWW
Year: 2010

In this paper we propose the Liquid Query paradigm, to support users in finding responses to multi-domain queries through exploratory information seeking across structured information sources (Web documents, deep Web data, and personal data repositories), wrapped by means of a uniform notion of search service. Liquid Query aims at filling the gap between general-purpose search engines, which are unable to find information spanning multiple topics, and domain-specific search systems, which cannot go beyond their domain limits. The Liquid Query interface consists of interaction primitives that let users pose questions and explore results spanning over multiple sources incrementally, thus getting closer and closer to the sought information. We demonstrate our approach with a prototype built upon the YQL (Yahoo! Query Language) framework.
Graph-based concept identification and disambiguation for enterprise search
Authors: Falk Brauer, Michael Huber 0001, Gregor Hackenbroich, Ulf Leser, Felix Naumann, Wojciech M. Barczynski
Venue: WWW
Year: 2010

Enterprise Search (ES) is different from traditional IR due to a number of reasons, among which the high level of ambiguity of terms in queries and documents and existence of graph-structured enterprise data (ontologies) that describe the concepts of interest and their relationships to each other, are the most important ones. Our method identifies concepts from the enterprise ontology in the query and corpus. We propose a ranking scheme for ontology sub-graphs on top of approximately matched token q-grams. The ranking leverages the graph-structure of the ontology to incorporate not explicitly mentioned concepts. It improves previous solutions by using a fine-grained ranking function that is specifically designed to cope with high levels of ambiguity. This method is able to capture much more of the semantics of queries and documents than previous techniques. We prove this claim by an evaluation of our method in three real-life scenarios from two different domains, and found it to consistently be superior both in terms of precision and recall.
Search is dead!: long live search
Authors: Andrei Z. Broder, Elizabeth F. Churchill, Marti A. Hearst, Barney Pell, Prabhakar Raghavan, Andrew Tomkins
Venue: WWW
Year: 2010

Back in the heady days of 1999 and WWW8 (Toronto) we held a panel titled "Finding Anything in the Billion Page Web: Are Algorithms the Key?" In retrospect the answer to this question seems laughably obvious - the search industry has burgeoned on a foundation of algorithms, cloud computing and machine learning. As we move into the second decade of this millennium, we are confronted with a dizzying array of new paradigms for finding content, including social networks and location-based search and advertising. This panel pulls together senior experts from academia and the major search principals to debate whether search will continue to look anything like the 2-keywords-give-10-blue-links paradigm that Google has popularized. What do emerging approaches and paradigms - natural language search, social search, location-based search - mean for the future of search in general?
Not so creepy crawler: easy crawler generation with standard xml queries
Authors: Franziska von dem Bussche, Klara A. Weiand, Benedikt Linse, Tim Furche, François Bry
Venue: WWW
Year: 2010

Web crawlers are increasingly used for focused tasks such as the extraction of data from Wikipedia or the analysis of social networks like last.fm. In these cases, pages are far more uniformly structured than in the general Web and thus crawlers can use the structure of Web pages for more precise data extraction and more expressive analysis.
A refreshing perspective of search engine caching
Authors: Berkant Barla Cambazoglu, Flavio Paiva Junqueira, Vassilis Plachouras, Scott A. Banachowski, Baoqiu Cui, Swee Lim, Bill Bridge
Venue: WWW
Year: 2010

Commercial Web search engines have to process user queries over huge Web indexes under tight latency constraints. In practice, to achieve low latency, large result caches are employed and a portion of the query traffic is served using previously computed results. Moreover, search engines need to update their indexes frequently to incorporate changes to the Web. After every index update, however, the content of cache entries may become stale, thus decreasing the freshness of served results. In this work, we first argue that the real problem in today's caching for large-scale search engines is not eviction policies, but the ability to cope with changes to the index, i.e., cache freshness. We then introduce a novel algorithm that uses a time-to-live value to set cache entries to expire and selectively refreshes cached results by issuing refresh queries to back-end search clusters. The algorithm prioritizes the entries to refresh according to a heuristic that combines the frequency of access with the age of an entry in the cache. In addition, for setting the rate at which refresh queries are issued, we present a mechanism that takes into account idle cycles of back-end servers. Evaluation using a real workload shows that our algorithm can achieve hit rate improvements as well as reduction in average hit ages. An implementation of this algorithm is currently in production use at Yahoo!.
Efficient resource allocation and power saving in multi-tiered systems
Authors: Andrew Caniff, Lei Lu, Ningfang Mi, Ludmila Cherkasova, Evgenia Smirni
Venue: WWW
Year: 2010

In this paper, we present Fastrack, a parameter-free algorithm for dynamic resource provisioning that uses simple statistics to promptly distill information about changes in workload burstiness. This information, coupled with the application's end-to-end response times and system bottleneck characteristics, guide resource allocation that shows to be very effective under a broad variety of burstiness profiles and bottleneck scenarios.
A generalized framework of exploring category information for question retrieval in community question answer archives
Authors: Xin Cao 0001, Gao Cong, Bin Cui 0001, Christian S. Jensen
Venue: WWW
Year: 2010

Community Question Answering (CQA) has emerged as a popular type of service where users ask and answer questions and access historical question-answer pairs. CQA archives contain very large volumes of questions organized into a hierarchy of categories. As an essential function of CQA services, question retrieval in a CQA archive aims to retrieve historical question-answer pairs that are relevant to a query question. In this paper, we present a new approach to exploiting category information of questions for improving the performance of question retrieval, and we apply the approach to existing question retrieval models, including a state-of-the-art question retrieval model. Experiments conducted on real CQA data demonstrate that the proposed techniques are capable of outperforming a variety of baseline methods significantly.
RankCompete: simultaneous ranking and clustering of web photos
Authors: Liangliang Cao, Andrey Del Pozo, Xin Jin 0001, Jiebo Luo 0001, Jiawei Han 0001, Thomas S. Huang
Venue: WWW
Year: 2010

With the explosive growth of digital cameras and online media, it has become crucial to design efficient methods that help users browse and search large image collections. The recent VisualRank algorithm [4] employs visual similarity to represent the link structure in a graph so that the classic PageRank algorithm can be applied to select the most relevant images. However, measuring visual similarity is difficult when there exist diversified semantics in the image collection, and the results from VisualRank cannot supply good visual summarization with diversity. This paper proposes to rank the images in a structural fashion, which aims to discover the diverse structure embedded in photo collections, and rank the images according to their similarity among local neighborhoods instead of across the entire photo collection. We design a novel algorithm named RankCompete, which generalizes the PageRank algorithm for the task of simultaneous ranking and clustering. The experimental results show that RankCompete outperforms VisualRank and provides an efficient but effective tool for organizing web photos.
Study language models with specific user goals
Authors: Rongwei Cen, Yiqun Liu 0001, Min Zhang 0006, Liyun Ru, Shaoping Ma
Venue: WWW
Year: 2010

Under different language contexts, people choose different terms or phrases to express their feelings and opinions. When a user is writing a paper or chatting with a friend, he/she applies a specific language model corresponding to the underlying goal. This paper presents a log-based study of analyzing the language models with specific goals. We exhibit the statistical information of terms and software programs, propose some methods to estimate the divergence of language models with specific user goals and measure the discrimination of these models. Experimental results show that the language models with different user goals have large divergence and different discrimination. These study conclusions can be applied to understand user needs and improve Human-Computer Interaction (HCI).
The paths more taken: matching DOM trees to search logs for accurate webpage clustering
Authors: Deepayan Chakrabarti, Rupesh R. Mehta
Venue: WWW
Year: 2010

An unsupervised clustering of the webpages on a website is a primary requirement for most wrapper induction and automated data extraction methods. Since page content can vary drastically across pages of one cluster (e.g., all product pages on amazon.com), traditional clustering methods typically use some distance function between the DOM trees representing a pair of webpages. However, without knowing which portions of the DOM tree are "important," such distance functions might discriminate between similar pages based on trivial features (e.g., differing number of reviews on two product pages), or club together distinct types of pages based on superficial features present in the DOM trees of both (e.g., matching footer/copyright), leading to poor clustering performance.
Navigational complexity in web interactions
Authors: Praphul Chandra, Geetha Manjunath
Venue: WWW
Year: 2010

As the web grows in size, interfaces & interactions across websites diverge - for differentiation and arguably for a better user experience. However, this size & diversity is also a cognitive load for the user who has to learn a new user interface for every new website she visits. Several studies have confirmed the importance of well designed websites. In this paper, we propose a method for quantitative evaluation of the navigational complexity of user interactions on the web. Our approach of quantifying interaction complexity exploits the modeling of the web as a graph and uses the information theoretic definition of complexity. It enables us to measure the navigational complexity of web interaction in bits. Our approach is structural in nature and can be applied to both traditional paradigm of web interaction (browsing) and to emerging paradigms of web interaction like web widgets.
Transfer learning for behavioral targeting
Authors: Tianqi Chen, Jun Yan 0001, Gui-Rong Xue, Zheng Chen 0001
Venue: WWW
Year: 2010

Recently, Behavioral Targeting (BT) is attracting much attention from both industry and academia due to its rapid growth in online advertising market. Though a basic assumption of BT, which is, the users who share similar Web browsing behaviors will have similar preference over ads, has been empirically verified, we argue that the users' ad click preference and Web browsing behavior are not reflecting the same user intent though they are correlated. In this paper, we propose to formulate BT as a transfer learning problem. We treat the users' preference over ads and Web browsing behaviors as two different user behavioral domains and propose to utilize transfer learning strategy across these two user behavioral domains to segment users for BT ads delivery. We show that some classical BT solutions could be formulated in transfer learning view. As an example, we propose to leverage translated learning, which is a recent proposed transfer learning algorithm, to benefit the BT ads delivery. Experimental results on real ad click data show that, BT user segmentation by the approach of transfer learning can outperform the classical user segmentation strategies for larger than 20% in terms of smoothed ad Click Through Rate(CTR).