Fuzzy Content Mining for Targeted Advertisement

Content-targeted advertising system is becoming an increasingly important part of the funding source of free web services. Highly efficient content analysis is the pivotal key of such a system. This project aims to establish a content analysis engine involving fuzzy logic that is able to automatically analyze real user-posted Web documents such as blog entries. Based on the analysis result, the system matches and retrieves the most appropriate Web advertisements. The focus and complexity is on how to better estimate and acquire the keywords that represent a given Web document. Fuzzy Web mining concept will be applied to synthetically consider multiple factors of Web content. A Fuzzy Ranking System is established based on certain fuzzy (and some crisp) rules, fuzzy sets, and membership functions to get the best candidate keywords. Once it is has obtained the keywords, the system will retrieve corresponding advertisements from certain providers through Web services as matched advertisements, similarly to retrieving a products list from Amazon.com. In 87% of the cases, the results of this system can match the accuracy of the Google Adwords system. Furthermore, this expandable system will also be a solid base for further research and development on this topic

On Web User Tracking: How Third-Party Http Requests Track Users' Browsing Patterns for Personalised Advertising

On today's Web, users trade access to their private data for content and services. Advertising sustains the business model of many websites and applications. Efficient and successful advertising relies on predicting users' actions and tastes to suggest a range of products to buy. It follows that, while surfing the Web users leave traces regarding their identity in the form of activity patterns and unstructured data. We analyse how advertising networks build user footprints and how the suggested advertising reacts to changes in the user behaviour.Comment: arXiv admin note: substantial text overlap with arXiv:1605.0653

CHORUS Deliverable 2.1: State of the Art on Multimedia Search Engines

Based on the information provided by European projects and national initiatives related to multimedia search as well as domains experts that participated in the CHORUS Think-thanks and workshops, this document reports on the state of the art related to multimedia content search from, a technical, and socio-economic perspective. The technical perspective includes an up to date view on content based indexing and retrieval technologies, multimedia search in the context of mobile devices and peer-to-peer networks, and an overview of current evaluation and benchmark inititiatives to measure the performance of multimedia search engines. From a socio-economic perspective we inventorize the impact and legal consequences of these technical advances and point out future directions of research

On web user tracking of browsing patterns for personalised advertising

This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Parallel, Emergent and Distributed Systems on 19/02/2017, available online: http://www.tandfonline.com/doi/abs/10.1080/17445760.2017.1282480On today’s Web, users trade access to their private data for content and services. App and service providers want to know everything they can about their users, in order to improve their product experience. Also, advertising sustains the business model of many websites and applications. Efficient and successful advertising relies on predicting users’ actions and tastes to suggest a range of products to buy. Both service providers and advertisers try to track users’ behaviour across their product network. For application providers this means tracking users’ actions within their platform. For third-party services following users, means being able to track them across different websites and applications. It is well known how, while surfing the Web, users leave traces regarding their identity in the form of activity patterns and unstructured data. These data constitute what is called the user’s online footprint. We analyse how advertising networks build and collect users footprints and how the suggested advertising reacts to changes in the user behaviour.Peer ReviewedPostprint (author's final draft

You never surf alone. Ubiquitous tracking of users' browsing habits

In the early age of the internet users enjoyed a large level of anonymity. At the time web pages were just hypertext documents; almost no personalisation of the user experience was o ered. The Web today has evolved as a world wide distributed system following specific architectural paradigms. On the web now, an enormous quantity of user generated data is shared and consumed by a network of applications and services, reasoning upon users expressed preferences and their social and physical connections. Advertising networks follow users' browsing habits while they surf the web, continuously collecting their traces and surfing patterns. We analyse how users tracking happens on the web by measuring their online footprint and estimating how quickly advertising networks are able to pro le users by their browsing habits