Accessible POI Recommendation Using Adaptive Aggregation of Binary Ratings

Everyone needs one or more forms of accessibility at some point in life due to age, medical conditions, accidents, etc. People with accessibility needs have the right to accessible services, as well as the right to information about accessibility at various places or Points of Interest (POI). While most popular POI recommendation services do not take accessibility into account, some of them only consider a few specific needs, such as ramp for wheelchair users. However, different users have different accessibility needs regarding the structure of the building, special aid devices, and facilities to be able to independently visit a place. The proposed system focuses on finding the personalized accessibility score for a (user, POI) pair. It can be used with other factors such as historical behavior, social influence, geographical conditions, etc. to recommend accessible places. It uses time decaying aggregate on the crowd-sourced binary rating data to find accurate approximation of current accessibility status for each accessibility criteria. Also, we propose a tunnel-based algorithm to detect the trend of binary stream data to update the rate of decay. This ensures that the calculated aggregate adapts to change in the accessibility status of the place

A Software Product Line Approach to Ontology-based Recommendations in E-Tourism Systems

This study tackles two concerns of developers of Tourism Information Systems (TIS). First is the need for more dependable recommendation services due to the intangible nature of the tourism product where it is impossible for customers to physically evaluate the services on offer prior to practical experience. Second is the need to manage dynamic user requirements in tourism due to the advent of new technologies such as the semantic web and mobile computing such that etourism systems (TIS) can evolve proactively with emerging user needs at minimal time and development cost without performance tradeoffs. However, TIS have very predictable characteristics and are functionally identical in most cases with minimal variations which make them attractive for software product line development. The Software Product Line Engineering (SPLE) paradigm enables the strategic and systematic reuse of common core assets in the development of a family of software products that share some degree of commonality in order to realise a significant improvement in the cost and time of development. Hence, this thesis introduces a novel and systematic approach, called Product Line for Ontology-based Tourism Recommendation (PLONTOREC), a special approach focusing on the creation of variants of TIS products within a product line. PLONTOREC tackles the aforementioned problems in an engineering-like way by hybridizing concepts from ontology engineering and software product line engineering. The approach is a systematic process model consisting of product line management, ontology engineering, domain engineering, and application engineering. The unique feature of PLONTOREC is that it allows common TIS product requirements to be defined, commonalities and differences of content in TIS product variants to be planned and limited in advance using a conceptual model, and variant TIS products to be created according to a construction specification. We demonstrated the novelty in this approach using a case study of product line development of e-tourism systems for three countries in the West-African Region of Africa

A collaborative filtering based persona identification in requirements elicitation

Persona is a fictional character that archetypically represents a user group. Persona identification is an important step in requirements elicitation. A review of related literature has shown that the persona is identified using qualitative approaches such as ethnographic profiling, user observations and user interviews. These approaches classify users on the basis of demographics or behavioral patterns. The drawbacks for such qualitative approaches are: they focus on detailed information gathering rather than correctly identifying representative user of persona; identified personas are too subjective as different requirements analysts may create different personas; these approaches do not scale well for a large number user involvement due to the high computational complexity of processing unstructured data. This paper proposed the collaborative filtering based persona-scenario (CFPS) approach to identify persona by calculating the similarities between the representative user to other users, combining the collaborative filtering algorithm and the persona-scenario approach. The case study shows the proposed approach improves the efficiency and accuracy in persona identification and requirements elicitation

Multi-Dimensional-Personalization in mobile contexts

During the dot com era the word "personalisation” was a hot buzzword. With the fall of the dot com companies the topic has lost momentum. As the killer application for UMTS or the mobile internet has yet to be identified, the concept of Multi-Dimensional-Personalisation (MDP) could be a candidate. Using this approach, a recommendation of mobile advertisement or marketing (i.e., recommendations or notifications), online content, as well as offline events, can be offered to the user based on their known interests and current location. Instead of having to request or pull this information, the new service concept would proactively provide the information and services – with the consequence that the right information or service could therefore be offered at the right place, at the right time. The growing availability of "Location-based Services“ for mobile phones is a new target for the use of personalisation. "Location-based Services“ are information, for example, about restaurants, hotels or shopping malls with offers which are in close range / short distance to the user. The lack of acceptance for such services in the past is based on the fact that early implementations required the user to pull the information from the service provider. A more promising approach is to actively push information to the user. This information must be from interest to the user and has to reach the user at the right time and at the right place. This raises new requirements on personalisation which will go far beyond present requirements. It will reach out from personalisation based only on the interest of the user. Besides the interest, the enhanced personalisation has to cover the location and movement patterns, the usage and the past, present and future schedule of the user. This new personalisation paradigm has to protect the user’s privacy so that an approach supporting anonymous recommendations through an extended "Chinese Wall“ will be described

Adaptive hypertext and hypermedia : workshop : proceedings, 3rd, Sonthofen, Germany, July 14, 2001 and Aarhus, Denmark, August 15, 2001

This paper presents two empirical usability studies based on techniques from Human-Computer Interaction (HeI) and software engineering, which were used to elicit requirements for the design of a hypertext generation system. Here we will discuss the findings of these studies, which were used to motivate the choice of adaptivity techniques. The results showed dependencies between different ways to adapt the explanation content and the document length and formatting. Therefore, the system's architecture had to be modified to cope with this requirement. In addition, the system had to be made adaptable, in addition to being adaptive, in order to satisfy the elicited users' preferences

Adaptive hypertext and hypermedia : workshop : proceedings, 3rd, Sonthofen, Germany, July 14, 2001 and Aarhus, Denmark, August 15, 2001

This paper presents two empirical usability studies based on techniques from Human-Computer Interaction (HeI) and software engineering, which were used to elicit requirements for the design of a hypertext generation system. Here we will discuss the findings of these studies, which were used to motivate the choice of adaptivity techniques. The results showed dependencies between different ways to adapt the explanation content and the document length and formatting. Therefore, the system's architecture had to be modified to cope with this requirement. In addition, the system had to be made adaptable, in addition to being adaptive, in order to satisfy the elicited users' preferences

Multicriteria Evaluation for Top-k and Sequence-based Recommender Systems

L'abstract è presente nell'allegato / the abstract is in the attachmen

From the web of data to a world of action

This is the author’s version of a work that was accepted for publication in Web Semantics: Science, Services and Agents on the World Wide Web. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Web Semantics: Science, Services and Agents on the World Wide Web 8.4 (2010): 10.1016/j.websem.2010.04.007This paper takes as its premise that the web is a place of action, not just information, and that the purpose of global data is to serve human needs. The paper presents several component technologies, which together work towards a vision where many small micro-applications can be threaded together using automated assistance to enable a unified and rich interaction. These technologies include data detector technology to enable any text to become a start point of semantic interaction; annotations for web-based services so that they can link data to potential actions; spreading activation over personal ontologies, to allow modelling of context; algorithms for automatically inferring 'typing' of web-form input data based on previous user inputs; and early work on inferring task structures from action traces. Some of these have already been integrated within an experimental web-based (extended) bookmarking tool, Snip!t, and a prototype desktop application On Time, and the paper discusses how the components could be more fully, yet more openly, linked in terms of both architecture and interaction. As well as contributing to the goal of an action and activity-focused web, the work also exposes a number of broader issues, theoretical, practical, social and economic, for the Semantic Web.Parts of this work were supported by the Information Society Technologies (IST) Program of the European Commission as part of the DELOS Network of Excellence on Digital Libraries (Contract G038- 507618). Thanks also to Emanuele Tracanna, Marco Piva, and Raffaele Giuliano for their work on On Time

The Challenges of Big Data - Contributions in the Field of Data Quality and Artificial Intelligence Applications

The term "big data" has been characterized by challenges regarding data volume, velocity, variety and veracity. Solving these challenges requires research effort that fits the needs of big data. Therefore, this cumulative dissertation contains five paper aiming at developing and applying AI approaches within the field of big data as well as managing data quality in big data