Data Portal @ linkeddatafragments.org

Matches in ScholarlyData for { ?s ?p ?o. }

• item-2 previous item-1.
• item-3 type ListItem.
• item-3 hasContent peter-moulder.
• item-3 next item-4.
• item-3 previous item-2.
• item-4 type ListItem.
• item-4 hasContent michael-wybrow.
• item-4 next item-5.
• item-4 previous item-3.
• item-5 type ListItem.
• item-5 hasContent tim-dwyer.
• item-5 previous item-4.
• 85 type InProceedings.
• 85 label "What's Up CAPTCHA? A CAPTCHA Based on Image Orientation".
• 85 sameAs 85.
• 85 abstract "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.".
• 85 hasAuthorList authorList.
• 85 isPartOf proceedings.
• 85 keyword "User Interfaces and Mobile Web".
• 85 title "What's Up CAPTCHA? A CAPTCHA Based on Image Orientation".
• authorList type List.
• authorList hasFirstItem item-1.
• authorList hasItem item-1.
• authorList hasItem item-2.
• authorList hasItem item-3.
• authorList hasLastItem item-3.
• item-1 type ListItem.
• item-1 hasContent rich-gossweiler.
• item-1 next item-2.
• item-2 type ListItem.
• item-2 hasContent maryam-kamvar.
• item-2 next item-3.
• item-2 previous item-1.
• item-3 type ListItem.
• item-3 hasContent shumeet-baluja.
• item-3 previous item-2.
• 86 type InProceedings.
• 86 label "Rapid Development of Spreadsheet-based Web Mashups".
• 86 sameAs 86.
• 86 abstract "The rapid growth of social networking sites and web communities have motivated web sites to expose their APIs to external developers who create mashups by assembling existing functionalities. Current APIs, however, aim toward developers with programming expertise; they are not directly usable by wider class of users who do not have programming background, but would nevertheless like to build their own mashups. To address this need, we propose a spreadsheet-based Web mashups development framework, which enables users to develop mashups in the popular spreadsheet environment. First, we provide a mechanism that makes structured data first class values of spreadsheet cells. Second, we propose a new component model that can be used to develop fairly sophisticated mashups, involving joining data sources and keeping spreadsheet data up to date. Third, to simplify mashup development, we provide a collection of spreadsheet-based mashup patterns that captures common Web data access and spreadsheet presentation functionalities. Users can reuse and customize these patterns to build spreadsheet-based Web mashups instead of developing them from scratch. Fourth, we enable users to manipulate structured data presented on spreadsheet in a drag-and-drop fashion. Finally, we have developed and tested a proof-of-concept prototype to demonstrate the utility of the proposed framework.".
• 86 hasAuthorList authorList.
• 86 isPartOf proceedings.
• 86 keyword "Web Engineering".
• 86 title "Rapid Development of Spreadsheet-based Web Mashups".
• authorList type List.
• authorList hasFirstItem item-1.
• authorList hasItem item-1.
• authorList hasItem item-2.
• authorList hasItem item-3.
• authorList hasItem item-4.
• authorList hasItem item-5.
• authorList hasLastItem item-5.
• item-1 type ListItem.
• item-1 hasContent woralak-kongdenfha.
• item-1 next item-2.
• item-2 type ListItem.
• item-2 hasContent boualem-benatallah.
• item-2 next item-3.
• item-2 previous item-1.
• item-3 type ListItem.
• item-3 hasContent julien-vayssiere.
• item-3 next item-4.
• item-3 previous item-2.
• item-4 type ListItem.
• item-4 hasContent regis-saint-paul.
• item-4 next item-5.
• item-4 previous item-3.
• item-5 type ListItem.
• item-5 hasContent fabio-casati.
• item-5 previous item-4.
• 87 type InProceedings.
• 87 label "Mashroom: End-User Mashup Programming Using Nested Tables".
• 87 sameAs 87.
• 87 abstract "This paper presents an end-user-oriented programming environment called Mashroom. Major contributions herein include an end-user programming model with an expressive data structure as well as a set of formally-defined mashup operators. The data structure takes advantage of nested table, and maintains the intuitiveness while allowing users to express complex data objects. The mashup operators are visualized with contextual menu and formula bar and can be directly applied on the data. Experiments and case studies reveal that end users have little difficulty in effectively and efficiently using Mashroom to build mashup applications.".
• 87 hasAuthorList authorList.
• 87 isPartOf proceedings.
• 87 keyword "Web Engineering".
• 87 title "Mashroom: End-User Mashup Programming Using Nested Tables".
• authorList type List.
• authorList hasFirstItem item-1.
• authorList hasItem item-1.
• authorList hasItem item-2.
• authorList hasItem item-3.
• authorList hasLastItem item-3.
• item-1 type ListItem.
• item-1 hasContent guiling-wang.
• item-1 next item-2.
• item-2 type ListItem.
• item-2 hasContent shaohua-yang.
• item-2 next item-3.
• item-2 previous item-1.
• item-3 type ListItem.
• item-3 hasContent yanbo-han.
• item-3 previous item-2.
• 88 type InProceedings.
• 88 label "Automated Construction of Web Accessibility Models from Transaction Click-streams".
• 88 sameAs 88.
• 88 abstract "Screen readers, the dominant assistive technology used by visually impaired people to access the Web, function by speaking out the content of the screen serially. Using screen readers for conducting online transactions can cause considerable information overload, because transactions, such as shopping and paying bills, typically involve a number of steps spanning several web pages. One can combat this overload by using a transaction model for web accessibility that presents only fragments of web pages that are needed for doing transactions. We can realize such a model by coupling a process automaton, encoding states of a transaction, with concept classifiers that identify page fragments "relevant" to a particular state of the transaction. In this paper we present a fully automated process that synergistically combines several techniques for transforming unlabeled click-stream data generated by transactions into a transaction model. These techniques include web content analysis to partition a web page into segments consisting of semantically related content, contextual analysis of data surrounding clickable objects in a page, and machine learning methods, such as clustering of page segments based on contextual analysis, statistical classification, and automata learning. The use of unlabeled click streams in building transaction models has important benefits: (i) visually impaired users do not have to depend on sighted users for creating manually labeled training data to construct the models; (ii) it is possible to mine personalized models from unlabeled transaction click-streams associated with sites that visually impaired users visit regularly; (iii) since unlabeled data is relatively easy to obtain, it is feasible to scale up the construction of domain-specific transaction models (e.g., separate models for shopping, airline reservations, bill payments, etc.); (iv) adjusting the performance of deployed models over time with new training data is also doable. We provide preliminary experimental evidence of the practical effectiveness of both domain-specific, as well as personalized accessibility transaction models built using our approach. Finally, this approach is applicable for building transaction models for mobile devices with limited-size displays, as well as for creating wrappers for information extraction from web sites.".
• 88 hasAuthorList authorList.
• 88 isPartOf proceedings.

• first
• previous
• next