OpenRaiser/Intern-Atlas huggingface dataset:
Actively predicting diverse search intent from user browsing behaviors
Authors: Zhicong Cheng, Bin Gao 0001, Tie-Yan Liu
Venue: WWW
Year: 2010

This paper is concerned with actively predicting search intent from user browsing behavior data. In recent years, great attention has been paid to predicting user search intent. However, the prediction was mostly passive because it was performed only after users submitted their queries to search engines. It is not considered why users issued these queries, and what triggered their information needs. According to our study, many information needs of users were actually triggered by what they have browsed. That is, after reading a page, if a user found something interesting or unclear, he/she might have the intent to obtain further information and accordingly formulate a search query. Actively predicting such search intent can benefit both search engines and their users. In this paper, we propose a series of technologies to fulfill this task. First, we extract all the queries that users issued after reading a given page from user browsing behavior data. Second, we learn a model to effectively rank these queries according to their likelihoods of being triggered by the page. Third, since search intents can be quite diverse even if triggered by the same page, we propose an optimization algorithm to diversify the ranked list of queries obtained in the second step, and then suggest the list to users. We have tested our approach on large-scale user browsing behavior data obtained from a commercial search engine. The experimental results have shown that our approach can predict meaningful queries for a given page, and the search performance for these queries can be significantly improved by using the triggering page as contextual information.
Stochastic models for tabbed browsing
Authors: Flavio Chierichetti, Ravi Kumar 0001, Andrew Tomkins
Venue: WWW
Year: 2010

We present a model of tabbed browsing that represents a hybrid between a Markov process capturing the graph of hyperlinks, and a branching process capturing the birth and death of tabs. We present a mathematical criterion to characterize whether the process has a steady state independent of initial conditions, and we show how to characterize the limiting behavior in both cases. We perform a series of experiments to compare our tabbed browsing model with pagerank, and show that tabbed browsing is able to explain 15-25% of the deviation between actual measured browsing behavior and the behavior predicted by the simple pagerank model. We find this to be a surprising result, as the tabbed browsing model does not make use of any notion of site popularity, but simply captures deviations in user likelihood to open and close tabs from a particular node in the graph.
Constructing travel itineraries from tagged geo-temporal breadcrumbs
Authors: Munmun De Choudhury, Moran Feldman, Sihem Amer-Yahia, Nadav Golbandi, Ronny Lempel, Cong Yu 0001
Venue: WWW
Year: 2010

Vacation planning is a frequent laborious task which requires skilled interaction with a multitude of resources. This paper develops an end-to-end approach for constructing intra-city travel itineraries automatically by tapping a latent source reflecting geo-temporal breadcrumbs left by millions of tourists. In particular, the popular rich media sharing site, Flickr, allows photos to be stamped by the date and time of when they were taken, and be mapped to Points Of Interest (POIs) by latitude-longitude information as well as semantic metadata (e.g., tags) that describe them.
The "Map Trap"?: an evaluation of map versus text-based interfaces for location-based mobile search services
Authors: Karen Church, Joachim Neumann, Mauro Cherubini, Nuria Oliver
Venue: WWW
Year: 2010

As the mobile Internet continues to grow, there is an increasing need to provide users with effective search and information access services. In order to build more effective mobile search services, we must first understand the impact that various interface choices have on mobile users. For example, the majority of mobile location-based search services are built on top of a map visualization, but is this intuitive design-decision the optimal interface choice from a human centric perspective? In order to tackle this fundamental design question, we have developed two proactive mobile search interfaces (one map-based and the other text-based) that utilize key mobile contexts to improve the search and information discovery experience of mobile users. In this paper, we present the results of an exploratory field study of these two interfaces - involving 34 users over a 1 month period - where we focus in particular on the impact that the type of user interface (e.g. map vs text) has on the search and information discovery experience of mobile users. We highlight the main usage results - including that maps are not the interface of choice for certain information access tasks - and outline key implications for the design of next generation mobile search services.
A client-server architecture for state-dependent dynamic visualizations on the web
Authors: Daniel M. Coffman, Danny Soroker, Chandra Narayanaswami, Aaron Zinman
Venue: WWW
Year: 2010

As sophisticated enterprise applications move to the Web, some advanced user experiences become difficult to migrate due to prohibitively high computation, memory, and bandwidth requirements. State-dependent visualizations of large-scale data sets are particularly difficult since a change in the client’s context necessitates a change in the displayed results. This paper describes a Web architecture where clients are served a session-specific image of the data, with this image divided into tiles dynamically generated by the server. This set of tiles is supplemented with a corpus of metadata describing the immediate vicinity of interest; additional metadata is delivered as needed in a progressive fashion in support and anticipation of the user’s actions. We discuss how the design of this architecture was motivated by the goal of delivering a highly responsive user experience. As an example of a complete application built upon this architecture, we present OrgMaps, an interactive system for navigating hierarchical data, enabling fluid, low-latency navigation of trees of hundreds of thousands of nodes on standard Web browsers using only HTML and JavaScript.
Malicious interface design: exploiting the user
Authors: Gregory J. Conti, Edward Sobiesk
Venue: WWW
Year: 2010

In an ideal world, interface design is the art and science of helping users accomplish tasks in a timely, efficient, and pleasurable manner. This paper studies the inverse situation, the vast emergence of deliberately constructed malicious interfaces that violate design best practices in order to accomplish goals counter to those of the user. This has become a commonplace occurrence both on and off the desktop, particularly on the web. A primary objective of this paper is to formally define this problem, including construction of a taxonomy of malicious interface techniques and a preliminary analysis of their impact on users. Findings are presented that gauge the self-reported tolerance and expectation levels of users with regard to malicious interfaces as well as the effectiveness and ease of use of existing countermeasures. A second objective of this paper is to increase awareness, dialogue, and research in a domain that we consider largely unexplored but critical to future usability of the WWW. Our results were accomplished through significant compilation of malicious interface techniques based on review of thousands of web sites and by conducting three surveys. Ultimately, this paper concludes that malicious interfaces are a ubiquitous problem that demands intervention by the security and human computer interaction communities in order to reduce the negative impact on the global user population.
Competing for users' attention: on the interplay between organic and sponsored search results
Authors: Cristian Danescu-Niculescu-Mizil, Andrei Z. Broder, Evgeniy Gabrilovich, Vanja Josifovski, Bo Pang 0001
Venue: WWW
Year: 2010

Queries on major Web search engines produce complex result pages, primarily composed of two types of information: organic results, that is, short descriptions and links to relevant Web pages, and sponsored search results, the small textual advertisements often displayed above or to the right of the organic results. Strategies for optimizing each type of result in isolation and the consequent user reaction have been extensively studied; however, the interplay between these two complementary sources of information has been ignored, a situation we aim to change. Our findings indicate that their perceived relative usefulness (as evidenced by user clicks) depends on the nature of the query. Specifically, we found that, when both sources focus on the same intent, for navigational queries there is a clear competition between ads and organic results, while for non-navigational queries this competition turns into synergy.
Web search engine metrics: (direct metrics to measure user satisfaction)
Authors: Ali Dasdan, Kostas Tsioutsiouliklis, Emre Velipasaoglu
Venue: WWW
Year: 2010

Search engines are important resources for finding information on the Web. They are also important for publishers and advertisers to present their content to users. Thus, user satisfaction is key and must be quantified. In this tutorial, we give a practical review of web search metrics from a user satisfaction point of view. We cover metrics for relevance, comprehensiveness, coverage, diversity, discovery freshness, content freshness, and presentation. We will also describe how these metrics can be mapped to proxy metrics for the stages of a generic search engine pipeline. The practitioners can apply these metrics readily and the researchers can get motivation for new problems to work on, especially in formalizing and refining metrics.
Hierarchical cluster visualization in web mapping systems
Authors: Jean-Yves Delort
Venue: WWW
Year: 2010

This paper presents a technique for visualizing large spatial data sets in Web Mapping Systems (WMS). The technique creates a hierarchical clustering tree, which is subsequently used to extract clusters that can be displayed at a given scale without cluttering the map. Voronoi polygons are used as aggregation symbols to represent the clusters. This technique retains hierarchical relationships between data items at different scales. In addition, aggregation symbols do not overlap, and their sizes and the number of points that they cover is controlled by the same parameter. A prototype has been implemented and tested showing the effectiveness of the method for visualizing large data sets in WMS.
Scalable techniques for document identifier assignment ininverted indexes
Authors: Shuai Ding 0006, Josh Attenberg, Torsten Suel
Venue: WWW
Year: 2010

Web search engines depend on the full-text inverted index data structure. Because the query processing performance is so dependent on the size of the inverted index, a plethora of research has focused on fast end effective techniques for compressing this structure. Recently, several authors have proposed techniques for improving index compression by optimizing the assignment of document identifiers to the documents in the collection, leading to significant reduction in overall index size.
TWC data-gov corpus: incrementally generating linked government data from data.gov
Authors: Li Ding 0001, Dominic DiFranzo, Alvaro Graves, James Michaelis, Xian Li 0003, Deborah L. McGuinness, James A. Hendler
Venue: WWW
Year: 2010

The Open Government Directive is making US government data available via websites such as Data.gov for public access. In this paper, we present a Semantic Web based approach that incrementally generates Linked Government Data (LGD) for the US government. In focusing on the trade-off between high quality LGD generation (requiring non-trivial human expert input) and massive LGD generation (requiring low human processing cost), our work is highlighted by the following features: (i) supporting low-cost and extensible LGD publishing for massive government data; (ii) using Social Semantic Web (Web3.0) technologies to incrementally enhance published LGD via crowdsourcing, and (iii) facilitating mash-ups by declaratively reusing cross-dataset mappings which usually are hard-coded in applications.
Enterprise and desktop search
Authors: Pavel A. Dmitriev, Pavel Serdyukov, Sergey Chernov 0001
Venue: WWW
Year: 2010

With the growing amount of information on users' desktops and increasing scale and complexity of intranets, Enterprise and Desktop Search are becoming two increasingly important Information Retrieval applications. While the challenges arising there are not completely different from those that the web community has faced for years, advanced web search solutions are often unable to address them properly. In this tutorial we give a research prospective on distinctive features of both Enterprise and Desktop Search, explain typical search scenarios, and review existing ranking techniques and algorithms.
How much is your personal recommendation worth?
Authors: Paul Dütting, Monika Henzinger, Ingmar Weber
Venue: WWW
Year: 2010

Suppose you buy a new laptop and, simply because you like it so much, you recommend it to friends, encouraging them to purchase it as well. What would be an adequate price for the vendor of the laptop to pay for your recommendation?
Privacy wizards for social networking sites
Authors: Lujun Fang, Kristen LeFevre
Venue: WWW
Year: 2010

Privacy is an enormous problem in online social networking sites. While sites such as Facebook allow users fine-grained control over who can see their profiles, it is difficult for average users to specify this kind of detailed policy.
A unified ontology-based web page model for improving accessibility
Authors: Ruslan R. Fayzrakhmanov, Max C. Göbel, Wolfgang Holzinger, Bernhard Krüpl, Robert Baumgartner
Venue: WWW
Year: 2010

Fast technological advancements and little compliance with accessibility standards by Web page authors pose serious obstacles to the Web experience of the blind user. We propose a unified Web document model that enables us to create a richer browsing experience and improved navigability for blind users. The model provides an integrated view on all aspects of a Web page and is leveraged to create a multi-axial user interface.
Query parsing in mobile voice search
Authors: Junlan Feng
Venue: WWW
Year: 2010

Mobile voice search is a fast-growing business. It provides users an easier way to search for information using voice from mobile devices. In this paper, we describe a statistical approach to query parsing to assure search effectiveness. The task is to segment speech recognition (ASR) output, including ASR 1-Best and ASR word lattices, into segments and associate each segment with needed concepts in the application. We train the models including concept prior probability, query segment generation probability, and query subject probability from application data such as query log and source database. We apply the learned models on a mobile business search application and demonstrate the robustness of query parsing to ASR errors.
RDF compression: basic approaches
Authors: Javier D. Fernández, Claudio Gutierrez 0001, Miguel A. Martínez-Prieto
Venue: WWW
Year: 2010

This paper studies the compressibility of RDF data sets. We show that big RDF data sets are highly compressible due to the structure of RDF graphs (power law), organization of URIs and RDF syntax verbosity. We present basic approaches to compress RDF data and test them with three well-known, real-world RDF data sets.
How google analytics and conventional cookie tracking techniques overestimate unique visitors
Authors: Max I. Fomitchev
Venue: WWW
Year: 2010

We report the results of the analysis of website traffic logs and argue that both unique IP address and cookies vastly overestimate unique visitors, e.g. by factor of 8 in our studies. Google Analytics 'absolute unique visitors' measure is shown to produce similar 6x overestimation. To address the problem we present a new model for relating unique visitors to IP address or cookies.
A novel traffic analysis for identifying search fields in the long tail of web sites
Authors: George Forman, Evan Kirshenbaum, Shyamsundar Rajaram
Venue: WWW
Year: 2010

Using a clickstream sample of 2 billion URLs from many thousand volunteer Web users, we wish to analyze typical usage of keyword searches across the Web. In order to do this, we need to be able to determine whether a given URL represents a keyword search and, if so, which field contains the query. Although it is easy to recognize 'q' as the query field in 'http://www.google.com/search?hl=en&q=music', we must do this automatically for the long tail of diverse websites. This problem is the focus of this paper. Since the names, types and number of fields differ across sites, this does not conform to traditional text classification or to multi-class problem formulations. The problem also exhibits highly non-uniform importance across websites, since traffic follows a Zipf distribution.
Shout out: integrating news and reader comments
Authors: Lisa M. Gandy, Nathan D. Nichols, Kristian J. Hammond
Venue: WWW
Year: 2010

A useful approach for enabling computers to automatically create new content is utilizing the text, media, and information already present on the World Wide Web. The newly created content is known as "machine-generated content". For example, a machine-generated content system may create a multimedia news show with two animated anchors presenting a news story; one anchor reads the news story with text taken from an existing news article, and the other anchor regularly interrupts with his or her own opinion about the story. In this paper, we present such a system, and describe in detail its strategy for autonomously extracting and selecting the opinions given by the second anchor.
A framework for trust establishment and assessment on the web of data
Authors: Qi Gao 0002, Geert-Jan Houben
Venue: WWW
Year: 2010

With the enormous and still growing amount of data and user interaction on the Web, it becomes more and more necessary for data consumers to be able to assess the trustworthiness of data on the Web. In this paper, we present a framework for trust establishment and assessment on the Web of Data. Different from many approaches that build trust metrics within networks of people, we propose a model to represent the trust in concrete pieces of web data for a specific consumer, in which also the context is considered. Further more, we provide three strategies for trust assessment based on the principles of Linked Data, to overcome the shortcomings of the conventional web of documents: i.e. the lack of semantics and interlinking.
Rants: a framework for rank editing and sharing in web search
Authors: Byron J. Gao, Joey Jan
Venue: WWW
Year: 2010

With a Wiki-like search interface, users can edit ranks of search results and share the edits with the rest of the world. This is an effective way of personalization, as well as a practice of mass collaboration that allows users to vote for ranking and improve search performance. Currently, there are several ongoing experimentation efforts from the industry, e.g., SearchWiki by Google and U Rank by Microsoft. Beyond that, there is little published research on this new search paradigm. In this paper, we make an effort to establish a framework for rank editing and sharing in the context of web search, where we identify fundamental issues and propose principled solutions. Comparing to existing systems, for rank editing, our framework allows users to specify not only relative, but also absolute preferences. For edit sharing, our framework provides enhanced flexibility, allowing users to select arbitrarily aggregated views. In addition, edits can be shared among similar queries. We present a prototype system Rants, that implements the framework and provides search services through the Google web search API.
QuickSuggest: character prediction on web appliances
Authors: Ullas Gargi, Rich Gossweiler
Venue: WWW
Year: 2010

As traditional media and information devices integrate with the web, they must suddenly support a vastly larger database of relevant items. Many devices use remote controls with on-screen keyboards which are not well suited for text entry but are difficult to displace. We introduce a text entry method which significantly improves text entry speed for on-screen keyboards using the same simple Up/Down/Left/Right/Enter interface common to remote controls and gaming devices used to enter text. The paper describes QuickSuggest's novel adaptive user interface, demonstrates quantitative improvements from simulation results on millions of user queries and shows ease of use and efficiency with no learning curve in user experiments.
On the high density of leadership nuclei in endorsement social networks
Authors: Guillermo Garrido, Francesco Bonchi, Aristides Gionis
Venue: WWW
Year: 2010

In this paper we study the community structure of endorsement networks, i.e., social networks in which a directed edge u → v is asserting an action of support from user u to user v. Examples include scenarios in which a user u is favoring a photo, liking a post, or following the microblog of user v.
Measuring the web crawler ethics
Authors: C. Lee Giles, Yang Sun 0002, Isaac G. Councill
Venue: WWW
Year: 2010

Web crawlers are highly automated and seldom regulated manually. The diversity of crawler activities often leads to ethical problems such as spam and service attacks. In this research, quantitative models are proposed to measure the web crawler ethics based on their behaviors on web servers. We investigate and define rules to measure crawler ethics, referring to the extent to which web crawlers respect the regulations set forth in robots.txt configuration files. We propose a vector space model to represent crawler behavior and measure the ethics of web crawlers based on the behavior vectors. The results show that ethicality scores vary significantly among crawlers. Most commercial web crawlers' behaviors are ethical. However, many commercial crawlers still consistently violate or misinterpret certain robots.txt rules. We also measure the ethics of big search engine crawlers in terms of return on investment. The results show that Google has a higher score than other search engines for a US website but has a lower score than Baidu for Chinese websites.
Tracking the random surfer: empirically measured teleportation parameters in PageRank
Authors: David F. Gleich, Paul G. Constantine, Abraham D. Flaxman, Asela Gunawardana
Venue: WWW
Year: 2010

PageRank computes the importance of each node in a directed graph under a random surfer model governed by a teleportation parameter. Commonly denoted alpha, this parameter models the probability of following an edge inside the graph or, when the graph comes from a network of web pages and links, clicking a link on a web page. We empirically measure the teleportation parameter based on browser toolbar logs and a click trail analysis. For a particular user or machine, such analysis produces a value of alpha. We find that these values nicely fit a Beta distribution with mean edge-following probability between 0.3 and 0.7, depending on the site. Using these distributions, we compute PageRank scores where PageRank is computed with respect to a distribution as the teleportation parameter, rather than a constant teleportation parameter. These new metrics are evaluated on the graph of pages in Wikipedia.