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300 Germanakos & Mourlas Copyright 2006, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. transform information into knowledge (constructing new cognitive frames) and if they could be characterized as a converger, diverger, assimilator, accommodator, wholist, analyst, verbalizer, or imager. The Visual and Cognitive Processing dimension is being distinguished from: Visual Attention Processing: It is composed from the pre-attentive and the limitedcapacity stage; the pre-attentive stage of vision subconsciously defines objects from visual primitives, such as lines, curvature, orientation, color, and motion, and allows definition of objects in the visual field. When items pass from the preattentive stage to the limited-capacity stage, these items are considered as selected. Interpretation of eye movement data is based on the empirically-validated assumption that when a person is performing a cognitive task, while watching a display, the location of his/her gaze corresponds to the symbol currently being processed in working memory and, moreover, that the eye naturally focuses on areas that are most likely to be informative. Control of Processing: It refers to the processes that identify and register goalrelevant information and block out dominant or appealing but actually irrelevant information. Speed of Processing: It refers to the maximum speed at which a given m e n t a l act may be efficiently executed (cognitive processing efficiency). Working Memory: It refers to the processes that enable a person to hold information in an active state while integrating it with other information until the current problem is solved. The Emotional Processing dimension is composed of these parameters that could determine a user s emotional state during the whole response process. This is vital so as to determine the level of adaptation (user needs per time interval) during the interaction process. These parameters include: Extroversion: Extraverts are sociable, active, self-confident, and uninhibited; while introverts, are withdrawn, shy, and inhibited. Conscientiousness: Conscientious individuals are organized, ambitious, determined, reliable, and responsible; while individuals low in conscientiousness are distractible, lazy, careless, and impulsive. Neuroticism: Individuals high in neuroticism are confident, clearthinking, alert, and content. Open to experience: Individuals who are open to experience are curious and with wide interests, inventive, original, and artistic; individuals who are not open to experience are conservative, cautious, and mild. Understanding of emotions: It is the cognitive processing of the emotions; it is the ability of understanding and analysis of the complex emotions and the chain reactions of the emotions, that is, how one emotion generates another.

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Adaptation and Personalization of Web-Based Multimedia Content 299 Copyright 2006, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. Figure 5. User perceptual preference characteristics Figure 6. Three-dimensional approach

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Adaptation and Personalization of Web-Based Multimedia Content 297 Copyright 2006, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. Perceptual User Requirements: This is the new element/dimension of the user profile. It contains all the visual attention and cognitive processes (cognitive and emotional processing parameters) that completes the user perception and fulfills the user profile. It is considered a vital element of the user profile since it identifies the aspects of the user that is very difficult to be revealed and measured but, however, might determine his/her exact preferences and lead to a more concrete, accurate, and optimized user segmentation. Traditional User Characteristics: This element is directly related to the Perceptual User Requirements element and provides the so-called t r a d i - tional characteristics of a user: knowledge, goals, background, experience, preferences, activities, demographic information (age, gender), socio-economic information (income, class, sector, etc.), and so forth. Both elements are completing the user profiling from the user s point of view. Device/Channel Characteristics: This element is referring to all the characteristics that referred to the device or channel that the user is using and contains information like: bandwidth, displays, text-writing, connectivity, size, power processing, interface and data entry, memory and storage space, latency (high/low), and battery lifetime. These characteristics are mostly referred to mobile users and are considered important for the formulation of a more integrated user profile, since it determines the technical aspects of it. Semantic Multimedia Content: This component is based on metadata describing the content (data) available from the Content Provider (back-end layer). In this way, a common understanding of the data, that is, semantic interoperability and openness is achieved. The data manipulated by the system/architecture is described using metadata that comprises of all needed information to unambiguously describe each piece of data and collections of data. This provides semantic interoperability and a human-friendly description of data. This component is directly related to the New User Profile component, providing together the most optimized personalized Web-based multimedia content result. It is consisted of three elements: Perceptual Provider Characteristics: It identifies the provider characteristics assigned to the Web-based multimedia content or multimedia based service. They are involving all these perceptual elements that the provider has been based upon for the design of the content (i.e., actual content/data of the service, layout preferences, content presentation, etc.) Semantic Content Properties: This element performs the identification and metadata description of Web-based multimedia content or multi-media-based service based on predetermined ontologies. It is implemented in a transparent manner, removing data duplication and the problem of data consistency. Streaming Media Properties: It contains data transition mechanisms and the databases. These databases contain the Web-based multimedia content or

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298 Germanakos & Mourlas Copyright 2006, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. multimedia-based services as supplied by the provider (without at this point being further manipulated or altered). Back-End Layer (Content Provider) This is the last layer of the architecture and is directly connected to the middle layer. It contains transition mechanisms and the databases of Web-based multimedia content or multimedia-based services as supplied by the provider without been through any further manipulation or alteration. The proposed three-layer architecture for adaptation and personalization of Web-based multimedia content will allow users to receive the Web-based multimedia content or multimedia-based service which they access in an adapted style according to their preferences, increasing in that way efficiency and effectiveness of use. Implementation Considerations So far, the functionality and interrelation of three-layer achitecture components that provide adapted and personalized Web-based content have been extensively investigated This section will focus on the concepts and parameters that take part in the construction of a comprehensive user profile, and how these could be used in order to collect all the relevant information. As it has already been mentioned, a lot of research has been done for the implementation of the traditional user profiling. Many adaptation and personalization techniques have been developed, and common semantic libraries have been set up that give basically specific and ad-hoc solutions.. However, to our knowledge, implementations that incorporate visual attention, cognitive, and emotional processing parameters to the user profile have not been reported as yet, and such parameters would definitely lead to a comprehensive accumulation of user perceptual preference characteristics and hence, provide users with more sustainable personalized content. Therefore, main emphasis in the following section is given to the construction of the new comprehensive user profiling, incorporating these user perceptual preference characteristics mentioned above. Further examining the middle layer of the proposed architecture and the Perceptual User Requirements element of the New User Profiling component, we can see that the User Perceptual Preference Characteristics could be described as a continuous mental processing starting with the perception of an object in the users attentional visual field (stimulus) and going through a number of cognitive, learning, and emotional processes giving the actual response to that stimulus. This is depicted in Figure 5. These processes formulate a three-dimensional approach to the problem, as depicted in Figure 6. The three dimensions created are the Learning Styles, the Visual and Cognitive Processing, and the Emotional Processing dimensions. The User Learning Processing dimension is a selection of the most appropriate and technologically feasible learning styles, such as Witkin s Field-Dependent and Field- Independent and Kolb s Learning Styles, being in a position to identify how users

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296 Germanakos & Mourlas Copyright 2006, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. whole processing has been completed, it returns the adapted results to the user. It is comprised of three elements: Content Presentation (or Adaptive Presentation): It adapts the content of a page to the characteristics of the user according to the user profile and personalization processing. The content is individually generated or assembled from pieces for each user, to contain additional information, prerequisite information, or comparative explanations by conditionally showing, hiding, highlighting, or dimming fragments on a page. The granularity may vary from word replacement to the substitution of pages to the application of different media. Content Alteration (or Adaptive Content Selection): When the user searches for a particular content, that is, related information to his/her profile, the system can adaptively select and prioritize the most relevant items. Link-Level Manipulation (or Adaptive Navigation Support): It provides methods that restrict the user s interactions with the content or techniques that aid the user in their understanding of the information space, aiming to provide either orientation or guidance (i.e. adaptive link, adaptive link hiding/ annotation). Orientation informs the user about his/her place in the information space, while guidance is related to a user s goal. Filtering: This component is considered the main link of the front-layer with the middle layer of the architecture. It actually transmits the data accumulated both directions. It is responsible for making the the low-level reconstruction and filtering of the content, based on the personalization rules created, and to deliver the content for adaptation. Middle Layer (Web-Based Multimedia Personalization) The middle layer is the main layer of the architecture and it is called Web-Based Multimedia Personalization . At this level all the requests are processed. This layer is responsible for the custom tailoring of information to be delivered to the users, taking into consideration their habits and preferences, as well as, for mobile users mostly, their location ( location-based ) and time ( time-based ) of access. The whole processing varies from security, authentication, user segmentation, multimedia content identification, to provider perceptual characteristics, user perceptions (visual, mental and emotional), and so forth. This layer accepts requests from the front-end and, after the necessary processing, either sends information back or communicates with the next layer (back-end) accordingly. The middle layer is comprised of the following two components: New User Profiling: It contains all the information related to the user, necessary for the Web Personalization processing. It is directly related to the Semantic Multimedia Content component and is composed of three elements:

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Adaptation and Personalization of Web-Based Multimedia Content 295 Copyright 2006, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. Figure 4. Adaptation and personalization of Web-based multimedia content architecture The current architecture, depicted in Figure 4, Adaptation and Personalization of Webbased Multimedia Content Architecture, is composed of three interrelated parts/layers. Each layer for the purpose of the infrastructure functionality may be composed of components, and each component may be broken down into elements, as detailed below: Front-End Layer (Entry Point and Content Reconstruction) The front-end layer is the primary layer, and it is the user access interface of the system. It is called Entry Point and Content Reconstruction , and it accepts multi-device requests. It enables the attachment of various devices on the infrastructure (such as mobile phones, PDAs, desktop devices, tablet PC, satellite handset, etc.) identifying their characteristics and preferences as well as the location of the user currently active (personalization/locationbased). It also handles multi-channel requests. Dut to the variety of multi-channel delivery (i.e., over the Web, telephone, interactive kiosks, WAP, MMS, SMS, satellite, and so on), this layer identifies the different characteristics of the channels. It directly communicates with the middle layer exchanging multi-purpose data. It consists of two components, each one assigned for a different scope: Adaptation: This component comprises of all the access-control data (for security reasons) and all the information regarding the user profile. These might include user preferences, geographical data, device model, age, business type, native language, context, and so forth. It is the entry point for the user, enabling the login to the architecture. This component is directly communicating with the middle layer where the actual verification and profiling for the user is taking place. Once the

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294 Germanakos & Mourlas Copyright 2006, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. Figure 3. Detailed view of the mPERSONA architecture techniques in a component-based fashion in order to provide a global personalization scheme for the wireless user. The mPERSONA is a flexible and scalable system that focuses towards the new era of wireless Internet and the moving user. The particular architecture uses autonomous and independent components avoiding this way tying up to specific wireless protocols (e.g., WAP). To achieve a high degree of independence and autonomy, mPERSONA is based on mobile agents and mobile computing models such as the client intercept model (Panayiotou & Samaras, 2004). The architectural components are distinguished based on their location and functionality: a) the Content description component (Figure 3: 2 & 6), creates and maintains the content s provider metadata structure that describes the actual content, (b) the Content selection component (Figure 3: 1 & 7), selects the content that will be presented to the user when applying his profile, (c) the Content reform component (Figure 3: 3 & 4), reforms and delivers the desired content in the needed (by the user s device) form, and (d) the User profile management component (Figure 3: 5), registers and manages user profiles. The user s profile is split into two parts: the device profile (covers the user s devices) and the theme profile (preferences). A Three-Layer Architecture for Adaptation and Personalization of Web-Based Multimedia Content Based on the above considerations, a three-layer architecture for adaptation and personalization of Web-based multimedia content will now be presented, trying to convey the essence and the peculiarities encapsulated, and further answering the question why adaptation and personalization of Web-based content is considered vital for the sustainable provision of quality multi-channel Web-based multimedia content/ multimedia-based services.

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Adaptation and Personalization of Web-Based Multimedia Content 293 Copyright 2006, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. business multimedia-based services), and generally is a relatively new area of research. Web personalization is the process of customizing the content and structure of a Web site to the specific needs of each user by taking advantage of the user s navigational behavior. Being a multi-dimensional and complicated area, a universal definition has not been agreed to date. Nevertheless, most of the definitions given to Web personalization (Cingil, Dogac, & Azgin, 2000; Kim, 2002) agree that the steps of the Web personalization process include: (1) the collection of Web data, (2) the modeling and categorization of these data (pre-processing phase), (3) the analysis of the collected data, and the determination of the actions that should be performed. Moreover, many argue that emotional or mental needs, caused by external influences, should also be taken into account. Web Personalization could be realized in one of two ways: (a) Web sites that require users to register and provide information about their interests, and (b) Web sites that only require the registration of users so that they can be identified (De Bra et al., 2004). The main motivation points for personalization can be divided into those that are primarily to facilitate the work, and those that are primarily to accommodate social requirements. The former motivational subcategory contains the categories of enabling access to information content, accommodating work goals, and accommodating individual differences, while the latter contains the categories of eliciting an emotional response and expressing identity. Personalization levels have been classified into: Link Personalization (involves selecting the links that are more relevant to the user, changing the original navigation space by reducing or improving the relationships between nodes), Content Personalization (user interface can present different information for different users providing substantive information in a node, other than link anchors), Context Personalization (the same information (node) can be reached in different situations), Authorized Personalization (different users have different roles and therefore they might have different access authorizations) and Humanized Personalization (involves human computer interaction) (Lankhorst et al., 2002; Rossi, Schwade, & Guimaraes, 2001). The technologies that are employed in order to implement the processing phases mentioned above as well as the Web personalization categories are distinguished into: Content-Based Filtering, Rule- Based Filtering, Collaborative Filtering, Web Usage Mining, Demographic-Based Filtering, Agent Technologies, and Cluster Models (Mobasher, 2002; Pazzani, 1999; Perkowitz & Etzioni, 2003). The use of the user model is the most evident technical similarity of Adaptive Hypermedia and Web Personalization to achieve their goal. However, the way they maintain the user profile is different; Adaptive Hypermedia requires a continuous interaction with the user, while Web Personalization employs algorithms that continuously follow the users navigational behavior without any explicit interaction with the user. Technically, two of the adaptation/personalization techniques used are the same. These are adaptivenavigation support (of Adaptive Hypermedia and else referred to as link-level adaptation) and Link Personalization (of Web Personalization) and adaptive presentation (of Adaptive Hypermedia and else referred to as content-level adaptation) and Content Personalization (of Web Personalization). An example of a Web personalization application for the wireless user is the mPERSONA system, depicted in Figure 3. The mPERSONA system architecture combines existing

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292 Germanakos & Mourlas Copyright 2006, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. Figure 2. INSPIRE s components and the interaction with the learner As mentioned earlier, successful adaptation attempts have been made in the e-learning research field to provide the students with adapted content according to their different learning styles or knowledge level and goals. A typical case of such a system could be considered the INSPIRE (Intelligent System for Personalized Instruction in a Remote Environment) architecture, see Figure 2, where throughout its interaction with the learner, the system dynamically generates lessons that gradually lead to the accomplishment of the learning goals selected by the learner (Papanikolaou, Grigoriadou, Kornilakis, & Magoulas, 2002). INSPSIRE architecture has been designed so as to facilitate knowledge communication between the learner and the system and to support its adaptive functionality. INSPIRE comprises of five different modules: (a) the Interaction Monitoring Module that monitors and handles learner s responses during his/her interaction with the system, (b) the Learner s Diagnostic Module that processes data recorded about the learner and decides on how to classify the learner s knowledge, (c) the Lesson Generation Module that generates the lesson contents according to learner s knowledge goals and knowledge level, (d) the Presentation Module which functions to generate the educational material pages sent to the learner, and (e) the Data Storage, which holds the Domain knowledge and the Learner s Model. Web Personalization Overview Web Personalization refers to the whole process of collecting, classifying, and analyzing Web data, and determining based on these the actions that should be performed so that the information is presented in a personalized manner to the user. As inferred from its name, Web Personalization refers to Web applications solely (with popular use in e- Data Storage Domain Knowledge Learner Model Lesson Generation Module Diagnostic Module Presentation Module Interaction Monitoring Module Lesson Presentation Learner s Response Data Storage

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Adaptation and Personalization of Web-Based Multimedia Content 291 Copyright 2006, Idea Group Inc. Copying or distributing in print or electronic forms without written permission of Idea Group Inc. is prohibited. Figure 1. Adaptive hypermedia techniques adaptivity by manipulating the link structure or by altering the presentation of information, based on a basis of a dynamic understanding of the individual user, represented in an explicit user model (Brusilovsky, 1996; De Bra et al., 1999; Eklund, & Sinclair, 2000). In 1996, Brusilovsky identified four user characteristics to which an Adaptive Hypermedia System should adapt. These were: user s knowledge, goals, background and hypertext experience, and user s preferences. In 2001, further two sources of adaptation were added to this list, user s interests and individual traits, while a third source of different nature having to deal with the user s environment had also been identified. Generally, Adaptive Hypermedia Systems can be useful in application areas where the hyperspace is reasonably large and the user population is relatively diverse in terms of the above user characteristics. A review by Brusilovsky has identified six specific application areas for adaptive hypermedia systems since 1996 (Brusilovsky, 2001). These are: educational hypermedia, on-line information systems, information retrieval systems, institutional hypermedia, and systems for managing personalized view in information spaces. Educational hypermedia and on-line information systems are the most popular, accounting for about two- thirds of the research efforts in adaptive hypermedia. Adaptation effects vary from one system to another. These effects are grouped into three major adaptation technologies: adaptive content selection (De Bra & Nejdl, 2004), adaptive presentation (or content-level adaptation), and adaptive navigation support (or link-level adaptation) (Brusilovsky, 2001; De Bra et al., 1999; Eklund & Sinclair, 2000) and are summarized in Figure 1.

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