Prediction, Recommendation and Group Analytics Models in the domain of Mashup Services and Cyber-Argumentation Platform

Mashup application development is becoming a widespread software development practice due to its appeal for a shorter application development period. Application developers usually use web APIs from different sources to create a new streamlined service and provide various features to end-users. This kind of practice saves time, ensures reliability, accuracy, and security in the developed applications. Mashup application developers integrate these available APIs into their applications. Still, they have to go through thousands of available web APIs and chose only a few appropriate ones for their application. Recommending relevant web APIs might help application developers in this situation. However, very low API invocation from mashup applications creates a sparse mashup-web API dataset for the recommendation models to learn about the mashups and their web API invocation pattern. One research aims to analyze these mashup-specific critical issues, look for supplemental information in the mashup domain, and develop web API recommendation models for mashup applications. The developed recommendation model generates useful and accurate web APIs to reduce the impact of low API invocations in mashup application development. Cyber-Argumentation platform also faces a similarly challenging issue. In large-scale cyber argumentation platforms, participants express their opinions, engage with one another, and respond to feedback and criticism from others in discussing important issues online. Argumentation analysis tools capture the collective intelligence of the participants and reveal hidden insights from the underlying discussions. However, such analysis requires that the issues have been thoroughly discussed and participant’s opinions are clearly expressed and understood. Participants typically focus only on a few ideas and leave others unacknowledged and underdiscussed. This generates a limited dataset to work with, resulting in an incomplete analysis of issues in the discussion. One solution to this problem would be to develop an opinion prediction model for cyber-argumentation. This model would predict participant’s opinions on different ideas that they have not explicitly engaged. In cyber-argumentation, individuals interact with each other without any group coordination. However, the implicit group interaction can impact the participating user\u27s opinion, attitude, and discussion outcome. One of the objectives of this research work is to analyze different group analytics in the cyber-argumentation environment. The objective is to design an experiment to inspect whether the critical concepts of the Social Identity Model of Deindividuation Effects (SIDE) are valid in our argumentation platform. This experiment can help us understand whether anonymity and group sense impact user\u27s behavior in our platform. Another section is about developing group interaction models to help us understand different aspects of group interactions in the cyber-argumentation platform. These research works can help develop web API recommendation models tailored for mashup-specific domains and opinion prediction models for the cyber-argumentation specific area. Primarily these models utilize domain-specific knowledge and integrate them with traditional prediction and recommendation approaches. Our work on group analytic can be seen as the initial steps to understand these group interactions

Deep Learning Framework for Online Interactive Service Recommendation in Iterative Mashup Development

Recent years have witnessed the rapid development of service-oriented computing technologies. The boom of Web services increases the selection burden of software developers in developing service-based systems (such as mashups). How to recommend suitable follow-up component services to develop new mashups has become a fundamental problem in service-oriented software engineering. Most of the existing service recommendation approaches are designed for mashup development in the single-round recommendation scenario. It is hard for them to update recommendation results in time according to developers' requirements and behaviors (e.g., instant service selection). To address this issue, we propose a deep-learning-based interactive service recommendation framework named DLISR, which aims to capture the interactions among the target mashup, selected services, and the next service to recommend. Moreover, an attention mechanism is employed in DLISR to weigh selected services when recommending the next service. We also design two separate models for learning interactions from the perspectives of content information and historical invocation information, respectively, as well as a hybrid model called HISR. Experiments on a real-world dataset indicate that HISR outperforms several state-of-the-art service recommendation methods in the online interactive scenario for developing new mashups iteratively.Comment: 15 pages, 6 figures, and 3 table

Pro Web 2.0 Mashups: Remixing Data and Web Services

XXXIII, 603 p. ; 24 cmLibro ElectrónicoEn cub.: Remix the Web to create cutting-edge web applicationsHow many times have you seen a web site and said, “This would be exactly what I wanted— if only . . .” If only you could combine the statistics here with data from your company’s earnings projections. If only you could take the addresses for those restaurants and plot them on one map. How often have you entered the date of a concert into your calendar with a single click instead of retyping? How often do you wish that you could make all the different parts of your digital world—your e-mail, your word processor documents, your photos, your search results, your maps, your presentations—work together more seamlessly? After all, it’s all digital and malleable information—shouldn’t it all just fit together? In fact, below the surface, all the data, web sites, and applications you use could fit together. This book teaches you how to forge those latent connections—to make the Web your own—by remixing information to create your own mashups. A mashup, in the words of the Wikipedia, is a web site or web application “that seamlessly combines content from more than one source into an integrated experience.”1 Learning how to draw content from the Web together into new integrated interfaces and applications, whether for yourself or for other others, is the central concern of this book.¿Cuántas veces ha visto usted a un sitio web y le dijo: "Esto sería exactamente lo que quería- si sólo. . . "Si sólo pudiera combinar las estadísticas aquí con los datos de las ganancias de su empresa proyecciones. Si tan sólo pudiera tener las direcciones de los restaurantes y colócalas en una mapa. ¿Cuántas veces has entrado en la fecha de un concierto en su calendario con un solo clic en lugar de volver a escribir? ¿Con qué frecuencia desea que usted podría hacer todas las diferentes partes de su mundo digital, el correo electrónico, los documentos procesador de textos, fotos, resultados de la búsqueda, sus mapas, sus presentaciones, trabajar juntos con mayor perfección? Después de todo, todo es digital y maleable que la información shouldn't a sólo encajan entre sí? De hecho, debajo de la superficie, todos los datos, sitios web, y aplicaciones que utiliza podría encajar. Este libro te enseña a forjar esas conexiones latentes a hacer de la web su propio por información remezcla para crear su propia mashups. Un mashup, en palabras de la Wikipedia, es un sitio web o aplicación web "que combina a la perfección el contenido de más de una fuente en una experiencia integrada. "1 Aprender a dibujar el contenido de la Web junto a nuevos interfaces integradas y aplicaciones, ya sea para usted o para otros, es el centro de preocupación de este libro.The modern Web is awash with data and services just waiting to be used, but how do you make effective use of all this information? The answer lies in APIs (such as Google Maps, Flickr, and Amazon Web Services) and remixing, or mashups. "Pro Web 2.0 Mashups: Remixing Data and Web Services" teaches you everything you need to create useful, dynamic real-world applications using APIs, web services, Ajax, web standards, and server-side languages. All you need to make full use of this book is basic knowledge of HTML, CSS, and JavaScript, and at least one server-side language (such as PHP or ASP.NET). Highlights include the following: Looks at the overall shape of todays Web from a developers point of view--what are its main features, and what is available for us to use to develop applications? Contains real-world examples of creating mashups using all the major APIs. Contains examples written in multiple server-side languages. What you'll learn Understand how the constituent parts of the modern Web fit together--web standards, Ajax, APIs, libraries, tagging, blogs, wikis, and more. Create different types of mashup, for example mapping mashups, search functionality, calendars, RSS/Atom feeds, social bookmarking, online storage systems, open document formats, and more. Build Web 2.0 applications using HTML, CSS, JavaScript, Ajax, server-side languages, APIs, and libraries Who is this book for? This book is for any web developer who is already comfortable with HTML, CSS, JavaScript, and at least one server-side language and wants to learn how to create Web 2.0 applications. About the Apress Pro Series The Apress Pro series books are practical, professionaltutorials to keep you on and moving up the professional ladder. You have gotten the job, now you need to hone your skills in these tough competitive times. The Apress Pro series expands your skills and expertise in exactly the areas you need. Master the content of a Pro book, and you will always be able to get the job done in a professional development project. Written by experts in their field, Pro series books from Apress give you the hard-won solutions to problems you will face in your professional programming career. Related Titles Beginning Google Maps Applications with PHP and Ajax: From Novice to Professional Beginning Google Maps Applications with Rails and Ajax: From Novice to Professional Building Flickr Applications with PHP Pro DOM Scripting with Ajax, APIs and Libraries Pro Ajax and the .NET 2.0 Platform Pro Ajax and Java Frameworks.About the Author xxi About the Technical Reviewer xxiii Acknowledgments xxv Introduction xxvii PART 1 Remixing Information Without Programming CHAPTER 1 Learning from Specific Mashups 3 Looking for Patterns in Mashups 3 Housingmaps.com5 What Is Being Combined? 5 Why Are the Constituent Elements Being Combined? What’s the Problem Being Solved? 5 Where Is the Remixing Happening? 6 How Are These Elements Being Combined? 6 Comparable Mashups 7 Google Maps in Flickr 7 What Is Being Combined? 8 Why Are the Constituent Elements Being Combined? What’s the Problem Being Solved? 8 How Are These Elements Being Combined? 12 Comparable Mashups 13 LibraryLookup Bookmarklet13 Configuring a LibraryLookup Bookmarklet 14 Invoking the LibraryLookup Bookmarklet 15 How Does This Mashup Work? 16 How Can This Mashup Be Extended?17 Comparable Mashups 18 Tracking Other Mashups 18 Summary 18 vii CHAPTER 2 Uncovering the Mashup Potential of Web Sites 21 What Makes Web Sites and Applications Mashable 22 Ascertaining the Fundamental Entities of the Web Site22 Public APIs and Existing Mashups 23 Use of Ajax 24 Embedded Scriptability 24 Browser Plug-Ins 25 Getting Data In and Out of the Web Site 25 The Community of Users and Developers 25 Mobile and Alternative Interfaces and the Skinnability of the Web Site 26 Documentation 26 Is the Web Site Run on Open Source? 26 Intellectual Property, Reusability, and Creative Commons 26 Tagging, Feeds, and Weblogging27 URL Languages of Web Sites27 Some Mashups Briefly Revisited 28 Flickr: The Fundamentally Mashup-Friendly Site 29 Resources in Flickr 29 Users and Photos 30 Data Associated with an Individual Photo 33 Tags 34 User’s Archive: Browsing Photos by Date 36 Sets 37 Collections37 Favorites 37 A User’s Popular Photos 38 Contacts 38 Groups 38 Account Management40 Browsing Through Flickr40 Search 41 Geotagged Photos in Flickr 42 The Flickr Organizer 43 Recent Activities44 Mailing Interfaces 44 Interfacing to Weblogs 44 Syndication Feeds: RSS and Atom 45 Mobile Access45 Third-Party Flickr Apps 45 viii CONTENTS Creative Commons Licensing 46 Cameras 46 The Mashup-by-URL-Templating-and-Embedding Pattern 47 Google Maps 49 URL Language of Google Maps 49 Viewing KML Files in Google Maps51 Connecting Yahoo! Pipes and Google Maps 51 Other Simple Applications of the Google Maps URL Language 52 Amazon 53 Amazon Items53 Lists 55 Tags 55 Subject Headings 55 del.icio.us 56 Screen-Scraping and Bots 58 Summary 60 CHAPTER 3 Understanding Tagging and Folksonomies61 Tagging in Flickr 62 Tags in Flickr 63 How Tags Are Used in Practice 63 Creating Your Own Tags 64 Syntax of Tags in Flickr 64 Potential Weaknesses of Tags 65 Singular and Plural Forms of Tags in Flickr 65 Hacking the Tagging System: Geotagging and Machine Tags 66 Interesting Apps Using Flickr Tags 67 Tagging in del.icio.us 67 Mechanics of Adding Tags in del.icio.us 68 Dealing with Case and Multiword Phrases 68 Getting More Information 69 Gathering Content Through Tags in Technorati71 Searching Technorati with Tags71 How Technorati Finds Tags on the Web 72 Word Inflections and Syntactic Constraints in Technorati Tags 72 Using Tags to Mash Up Flickr and del.icio.us 72 Other Systems That Use Tagging 73 Relationship of Tags to Formal Classification Schemes 73 Summary 75 CONTENTS ix CHAPTER 4 Working with Feeds, RSS, and Atom77 What Are Feeds, and Why Are They Important? 78 RSS 2.0 78 RSS 1.0 80 Atom 1.0 82 Extensions to RSS 2.0 and Atom 1.0 84 Feeds from Flickr86 Flickr Feed Parameters 86 Examining the Flickr Feeds 87 Exchange Formats Other Than RSS and Atom 90 Feeds from Other Web Sites 92 Finding Feeds and Feed Autodiscovery 93 Feeds from Weblogs 94 Wikipedia Feeds94 Google and Yahoo! News 95 News Aggregators: Showing Flickr Feeds Elsewhere 96 Validating Feeds98 Scraping Feeds Using GUI Tools 98 Remixing Feeds with Feedburner 99 Remixing Feeds with Yahoo! Pipes 100 A Simple First Pipe with Yahoo! News 101 Google News and Refactoring Pipes102 Wikinews and NY Times: Filtering Feeds 103 Pulling the Feeds Together 104 Summary 104 CHAPTER 5 Integrating with Blogs 105 Integration Scenarios for Blogs 105 Sending Flickr Pictures to Blogs 106 Configuring Flickr for Integration with Blogs107 Blogging a Flickr Picture110 How Does the Flickr Blog Integration Work?110 Desktop Blogging Tools 111 Combining Feeds and Blogging to Generate Feedback Flows113 Flock: Bringing Together Blogs and Flickr 114 RSD: Discoverability of Blog APIs 115 Linkbacks 116 Wiki Integration at an Early Stage 116 Summary 117 x CONTENTS PART 2 Remixing a Single Web Application Using Its API CHAPTER 6 Learning Web Services APIs Through Flickr 121 An Introduction to the Flickr API 122 What Does This XML Response Mean? 124 What Can You Do with the XML Response? 126 API Documentation, Community, and Policy 128 Terms of Use for the API 128 Using the Flickr API Explorer and Documentation 129 Calling a Basic Flickr API Method from PHP 132 HTTP Clients 133 A Refresher on HTTP 134 XML Processing 138 Pulling It All Together: Generating Simple HTML Representations of the Photos 143 Where Does This Leave Us?145 The Flickr API in General 145 Using flickr.reflection Methods 146 Querying the Flickr Reflection Methods with PHP 149 Request and Response Formats 154 Flickr Authorization 156 Why Passing Passwords Around Doesn’t Work Too Well157 Authorization for Web Apps 157 Using Flickr API Kits 165 PEAR::Flickr_API 165 phpFlickr 166 Phlickr 168 Limitations of the Flickr API 169 Summary 170 CHAPTER 7 Exploring Other Web APIs 171 XML-RPC172 What’s Happening on the Wire? 176 Using Wireshark and curl to Analyze and Formulate HTTP Messages 177 Parsing XML-RPC Traffic178 CONTENTS xi SOAP 181 The Dream: Plug-and-Go Functionality Through WSDL and SOAP 181 geocoder.us 182 Amazon ECS 191 The Flickr API via SOAP195 Learning About Specific Web APIs 195 Programmableweb.com 196 YouTube 198 GData and the Blogger API 199 Using the Blogger API As a Uniform Interface Based on HTTP Methods203 Summary 204 CHAPTER 8 Learning Ajax/JavaScript Widgets and Their APIs 205 What You Need to Know206 What Difference Does Ajax Make? 207 Learning Firebug, DOM Inspector, and JavaScript Shell 208 Using the DOM Inspector 208 Using the Firebug Extension for Firefox 208 Using the JavaScript Shell 210 Working with JavaScript Libraries 210 YUI Widgets211 Using the YUI Calendar 211 Installing YUI on Your Host 212 Learning Google Maps 213 Accessing Flickr via JavaScript217 Using Greasemonkey to Access New York Times Permalinks 220 Learning More About JavaScript and Ajax 223 Summary 223 PART 3 Making Mashups CHAPTER 9 Moving from APIs and Remixable Elements to Mashups 227 Getting Oriented to ProgrammableWeb 228 User-Generated Data in ProgrammableWeb 228 Can Any Directory of Mashups Keep Up? 228 Learning About the Overall Mashup Scene 229 xii CONTENTS Directory of Mashups 230 Using Feeds to Track Mashups 230 Using Tags to Describe Mashups 231 API and Mashup Verticals 233 Looking at a Specific Mashup Profile233 Going from a Specific API to Mashups234 Sample Problems to Solve Using Mashups235 Tracking Interesting Books235 Knowing When to Buy Airplane Tickets 239 Finding That Dream House240 Mapping Breaking News 241 Summary 242 CHAPTER 10 Creating Mashups of Several Services 243 The Design 244 Background: Geotagging in Flickr245 Background: XMLHttpRequest and Containing Libraries 248 Using XMLHttpRequest Directly248 Using the YUI Connection Manager250 Building a Server-Side Proxy253 What Happens with XHR and Direct API Calls?253 Building a Server-Side Script for Geolocated Photos255 Building a Simple Client-Side Frame 257 Reading and Writing Elements257 Handling Simple Events to Connect Form Input and Display Calculations 260 Hooking the Client-Side Framework to Flickr 261 Writing a URL for Querying flickrgeo.php 262 Using XHR via the YUI Connection Manager to Read the JSON 262 Converting the JSON to HTML 264 Mashing Up Google Maps API with Flickr 266 Setting Up a Basic Google Map 267 Making the Map Respond to Changes in the Viewport of the Map268 Bringing Together the Flickr and GMap Code 269 Wiring Up the Bounding Box of the Google Map270 Making the Pictures Show Up in the Map 272 Google Mapplet That Shows Flickr Photos 277 Summary 281 CONTENTS xiii CHAPTER 11 Using Tools to Create Mashups 283 The Problem Mashup Tools Solve284 What You Are Making in This Chapter 284 Making the Mashup: A Step-by-Step Example286 Familiarizing Yourself with the Google Mashup Editor287 Reading and Displaying a Feed (Simple Template) 288 Introducing a Custom Template289 Using Yahoo! Pipes to Access Flickr 291 Displaying Flickr Photos Using 292 Adding JavaScript to the Mashup 294 How to Persist Feeds and Use Tabs 299 The Final Product: Showing the Saved Entries on a Map 304 Analysis of Trade-Offs in Using GME and Yahoo! Pipes309 Other Mashup Tools 310 Summary 311 CHAPTER 12 Making Your Web Site Mashable313 Why Make Your Web Site Mashable? 314 Using Techniques That Do Not Depend on APIs 314 Use a Consistent and Rich URL Language314 Use W3C Standards to Develop Your Web Site 315 Pay Attention to Web Accessibility315 Consider Allowing Users to Tag Your Content 315 Make Feeds Available 315 Make It Easy to Post Your Content to Blogs and Other Web Sites 316 Encourage the Sharing of Content with Explicit Licenses317 Develop Extensive Import and Export Options for User Content 317 Study How Users Remix Your Content and Make It Easier to Do So 317 Creating a Mashup-Friendly API 317 Learn From and Emulate Other APIs318 Keep in Mind Your Audiences for the API 318 Make Your API Easy to Learn 318 Test the Usability of Your API 319 Build a Granular, Loosely Coupled Architecture So That Creating an API Serves You As Much As It Does Others319 Embrace REST But Also Support SOAP and XML-RPC If You Can 320 xiv CONTENTS Consider Using the Atom Publishing Protocol As a Specific Instantiation of REST 320 Encourage the Development of API Kits: Third Party or In-House320 Support Extensive Error Reporting in Your APIs 321 Accept Multiple Formats for Output and Input 321 Support UI Functionality in the API 321 Include a Search API for Your Own Site 321 Version Your API 322 Foster a Community of Developers322 Don’t Try to Be Too Controlling in Your API322 Consider Producing a Service-Level Agreement (SLA) 322 Help API Users Consume Your Resources Wisely 323 Consider Open Sourcing Your Application 323 Easy-to-Understand Data Standards 323 Summary 324 PART 4 Exploring Other Mashup Topics CHAPTER 13 Remixing Online Maps and 3D Digital Globes327 The Number of Online Maps 328 Examples of Map-Based Mashups329 Making Maps Without Programming 329 Mapbuilder.net 329 Google My Maps 331 A Mashup Opportunity: Mapping Yahoo! Local Collections332 Transforming the Yahoo! Local XML into CSV for Mapbuilder.net 334 Collection Building in Microsoft’s Live Search Maps 336 Summary of Making Maps Without Programming 338 Data Exchange Formats 338 CSV338 Microformats and Metatags for HTML 338 GeoRSS 339 Yahoo!’s Use of GeoRSS and Yahoo! YMaps Extensions 341 KML 345 Interoperability Among Formats: GeoRSS vsKML346 CONTENTS xv Creating Maps by API Programming 346 Google Maps API 347 Yahoo! Maps API351 Microsoft’s Live Search Maps/Virtual Earth354 Geocoding356 Yahoo! Maps 356 Geocoder.us 357 Google Geocoder 358 Virtual Earth 361 Geocoding Non-U.SAddresses363 Google Earth and KML 364 Displaying and Handling KML As End Users 364 KML 368 Programming Google Earth via COM and AppleScript374 Mapstraction and OpenLayers 376 An Integrative Example: Showing Flickr Pictures in Google Earth376 KML NetworkLink 379 Generating the KML for the Photos382 The flickrgeo.php Code383 Summary 393 CHAPTER 14 Exploring Social Bookmarking and Bibliographic Systems 395 The Social Bookmarking Scene 396 Using Programmableweb.com to Examine the Popularity of APIs 396 del.icio.us 397 Using the del.icio.us API 398 Third-Party Tools for del.icio.us405 Third-Party API Kits 405 Yahoo! Bookmarks and MyWeb407 Connotea408 A Flickr and del.icio.us Mashup 412 Summary 416 CHAPTER 15 Accessing Online Calendars and Event Aggregators 417 Google Calendar 418 Setting Up Google Calendar As an End User 418 Exploring the Feed Formats from Google Calendar 420 xvi CONTENTS Using the GData-Based Calendar API Directly 426 Using the PHP API Kit for Google Calendar 434 Using the Python API Kit for Google Calendar 437 30boxes.com 438 An End User Tutorial 439 30boxes.com API 439 Event Aggregators 443 Upcoming.yahoo.com 443 Eventful.com452 Programming with iCalendar 458 Python and iCalendar 458 PHP and iCalendar 460 Exporting an Events Calendar to iCalendar and Google Calendar461 The Source: UC Berkeley Event Calendars 462 Creating an iCalendar Feed of Critic’s Choice Using Python462 Writing the Events to Google Calendar464 Summary 471 CHAPTER 16 Using Online Storage Services 473 Introducing Amazon S3 473 Rationale for S3 474 Conceptual Structure of Amazon S3 475 The Firefox S3 Extension Gets You Started with S3476 Using the S3 REST Interface 477 Listing Buckets Using the REST Interface 480 Using the SOAP Interface to S3481 Amazon S3 API Kits 482 PHP 483 Python 484 Summary 486 CHAPTER 17 Mashing Up Desktop and Web-Based Office Suites 487 Mashup Scenarios for Office Suites 487 The World of Document Markup 488 The OpenDocument Format488 Learning Basic ODF Tags 497 Create an ODF Text Document Without Any Styling of ODF Elements 499 Setting the Paragraph Text to text-body 503 CONTENTS xvii Formatting Lists to Distinguish Between Ordered and Unordered Lists504 Getting Bold, Italics, Font Changes, and Color Changes into Text Spans 505 API Kits for Working with ODF 507 Odfpy 507 OpenDocumentPHP 516 Leveraging OO.o to Generate ODF 518 ECMA Office Open XML (OOXML) 519 Viewers/Validators for OOXML522 Comparing ODF and OOXML 522 Online Office Suites523 Usage Scenarios for Programmable Online Spreadsheets 523 Google Spreadsheets API 524 Python API Kit 524 Mashup: Amazon Wishlist and Google Spreadsheets Mashup528 Zend PHP API Kit for Google Spreadsheets 533 A Final Variation: Amazon Wishlist to Microsoft Excel via COM 535 Zoho APIs 536 Summary 536 CHAPTER 18 Using Microformats and RDFa As Embeddable Data Formats537 Using Operator to Learn About Microformats 537 adr (Addresses) 540 hCard (Contacts) 541 hCalendar (Events)542 geo (Locations)543 tag (Tagspaces) 543 Definitions and Design Goals of Microformats 543 Microformats Design Patterns545 rel-design-pattern 545 class-design-pattern 545 abbr-design-pattern 546 include-pattern546 Examples of Microformats 547 rel-license 547 rel-tag 548 xfn548 xviii CONTENTS xFolk549 geo 549 hCard and adr550 hCalendar 551 Other Microformats 551 Microformats in Practice 552 Programming with Microformats 552 Language-Specific Libraries 552 Writing an Operator Script 553 Studying the Tutorial Script 554 Writing a Geocoding Script556 Resources (RDFa): A Promising Complement to Microformats 557 Reference for Further Study 558 Summary 558 CHAPTER 19 Integrating Search 559 Google Ajax Search 559 Manipulating Search Results 559 Yahoo! Search 561 Yahoo! Images 563 Microsoft Live.com Search 564 OpenSearch 568 Google Desktop HTTP/XML Gateway 570 Summary 571 APPENDIX 573 INDEX 57

Information-seeking on the Web with Trusted Social Networks - from Theory to Systems

This research investigates how synergies between the Web and social networks can enhance the process of obtaining relevant and trustworthy information. A review of literature on personalised search, social search, recommender systems, social networks and trust propagation reveals limitations of existing technology in areas such as relevance, collaboration, task-adaptivity and trust. In response to these limitations I present a Web-based approach to information-seeking using social networks. This approach takes a source-centric perspective on the information-seeking process, aiming to identify trustworthy sources of relevant information from within the user's social network. An empirical study of source-selection decisions in information- and recommendation-seeking identified five factors that influence the choice of source, and its perceived trustworthiness. The priority given to each of these factors was found to vary according to the criticality and subjectivity of the task. A series of algorithms have been developed that operationalise three of these factors (expertise, experience, affinity) and generate from various data sources a number of trust metrics for use in social network-based information seeking. The most significant of these data sources is Revyu.com, a reviewing and rating Web site implemented as part of this research, that takes input from regular users and makes it available on the Semantic Web for easy re-use by the implemented algorithms. Output of the algorithms is used in Hoonoh.com, a Semantic Web-based system that has been developed to support users in identifying relevant and trustworthy information sources within their social networks. Evaluation of this system's ability to predict source selections showed more promising results for the experience factor than for expertise or affinity. This may be attributed to the greater demands these two factors place in terms of input data. Limitations of the work and opportunities for future research are discussed

Review of the state of the art: discovering and associating semantics to tags in folksonomies

This paper describes and compares the most relevant approaches for associating tags with semantics in order to make explicit the meaning of those tags. We identify a common set of steps that are usually considered across all these approaches and frame our descriptions according to them, providing a unified view of how each approach tackles the different problems that appear during the semantic association process. Furthermore, we provide some recommendations on (a) how and when to use each of the approaches according to the characteristics of the data source, and (b) how to improve results by leveraging the strengths of the different approaches

A treatise on Web 2.0 with a case study from the financial markets

There has been much hype in vocational and academic circles surrounding the emergence of web 2.0 or social media; however, relatively little work was dedicated to substantiating the actual concept of web 2.0. Many have dismissed it as not deserving of this new title, since the term web 2.0 assumes a certain interpretation of web history, including enough progress in certain direction to trigger a succession [i.e. web 1.0 → web 2.0]. Others provided arguments in support of this development, and there has been a considerable amount of enthusiasm in the literature. Much research has been busy evaluating current use of web 2.0, and analysis of the user generated content, but an objective and thorough assessment of what web 2.0 really stands for has been to a large extent overlooked. More recently the idea of collective intelligence facilitated via web 2.0, and its potential applications have raised interest with researchers, yet a more unified approach and work in the area of collective intelligence is needed. This thesis identifies and critically evaluates a wider context for the web 2.0 environment, and what caused it to emerge; providing a rich literature review on the topic, a review of existing taxonomies, a quantitative and qualitative evaluation of the concept itself, an investigation of the collective intelligence potential that emerges from application usage. Finally, a framework for harnessing collective intelligence in a more systematic manner is proposed. In addition to the presented results, novel methodologies are also introduced throughout this work. In order to provide interesting insight but also to illustrate analysis, a case study of the recent financial crisis is considered. Some interesting results relating to the crisis are revealed within user generated content data, and relevant issues are discussed where appropriate

Assisted Reuse of Pattern-Based Composition Knowledge for Mashup Development

First generation of the World Wide Web (WWW) enabled users to have instantaneous access to a large diversity of knowledge. Second generation of the WWW (Web 2.0) brought a fundamental change in the way people interact with and through the World Wide Web. Web 2.0 has made the World Wide Web a platform not only for communication and sharing information but also for software development (e.g., web service composition). Web mashup or mashup development is a Web2.0 development approach in which users are expected to create applications by combining multiple data sources, application logic and UI components from the web to cater for their situational application needs. However, in reality creating an even simple mashup application is a complex task that can only be managed by skilled developers. Examples of ready mashup models are one of the main sources of help for users who don't know how to design a mashup, provided that suitable examples can be found (examples that have an analogy with the modeling situation faced by the user). But also tutorials, expert colleagues or friends, and, of course, Google are typical means to find help. However, searching for help does not always lead to a success, and retrieved information is only seldom immediately usable as it is, since the retrieved pieces of information are not contextual, i.e., immediately applicable to the given modeling problem. Motivated by the development challenges faced by a naive user of existing mashup tools, in this thesis we propose toaid such users by enabling assisted reuse of pattern-based composition knowledge. In this thesis we show how it is possible to effectively assist these users in their development task with contextual, interactive recommendations of composition knowledge in the form of mashup model patterns. We study a set of recommendation algorithms with different levels of performance and describe a flexible pattern weaving approach for the one-click reuse of patterns. We prove the generality of our algorithms and approach by implementing two prototype tools for two different mashup platforms. Finally, we validate the usefulness of our assisted development approach by performing thorough empirical tests and two user studies with our prototype tools