Modelling of an Adaptive Hypermedia System Based on Active Rules

Modelling of an Adaptive Hypermedia System Based on Active Rules Hussein Raad and Bernard Causse LIUPPA Université de Pau BP 576 64010 Pau cedex Tel : 01.47.98.72.84 raadhussein@hotmail.com Bernard.Causse@iutbay.univ-pau.fr Abstract. This paper is a contribution to the modelling of adaptive hypermedia. The main feature of such a system is able to construct its adaptive behaviour easily. It is based on the concept of the active rule (Event-Condition-Action). The advantage of this concept resides in the integration of all existing adaptation techniques in the system. Furthermore, this system allows introducing new adaptation strategies easily. The system architecture consists of three main parts: first the traditional hypermedia subsystem that contains the navigational model, the interface model, and the multimedia resources; second the adaptive subsystem that contains the user model, the semantic network model, the events analyser, and the adaptive behaviour specification entity; third the tasks model which contain the strategic rules bases associated with the adaptive behaviour specification entity, the navigational rules bases associated with the navigational model, and the interface rules bases associated with the interface model. 1 Introduction The emerging research domain Adaptive Hypermedia Systems (AHS) aims mainly to bridge the gap between traditional hypermedia systems and adaptive system. The goal of AHS is to help a wide range of users in a knowledge context largely diffused. This study aims to model AHS based on the active rules (Event-Condition-Action). The paper reviews the literature of the adaptation methods, discusses the general aspects of the approach being adopted in the existing AHSs and proposes the general architecture of our AHS. 2 Adaptation Methods We can distinguish between two adaptation methods: the first is based on the contents level (the so-called adaptive presentation); and the second is a link-based adaptation (the so-called adaptive navigation). S.A. Cerri, G. Gouardères, and F. Paraguaçu (Eds.): ITS 2002, LNCS 2363, pp. 149 157, 2002. Springer-Verlag Berlin Heidelberg 2002

150 H. Raad and B. Causse 2.1 Adaptive Presentation The idea is to adapt the content of a page accessed by a particular user to the current knowledge level, goals, and other characteristics of the user. Four techniques can be distinguished: additional, prerequisite, comparative and sorting explanations. 2.1.1 Additional Explanations It is the addition of particular information to the basic content of a page. This information explains a concept that is related to a category of the users. The additional explanations can be presented or hidden according to the level of this category. This technique is used in the following systems: MetaDoc, KN-AHS, IPIAIM and Anatom-Tutor. 2.1.2 Prerequisite Explanations This technique is based on the principle of the prerequisite links between the semantic concepts. Before presenting a concept explanation, the system inserts the explanations concerning the prerequisite concepts to facilitate the comprehension of this concept. The systems which apply this technique are Lisp-Critic and C-book. 2.1.3 Comparative Explanations This technique is based on the principle of the similar links between the concepts. If there are two similar concepts, a comparative explanation can be offered to the user to show the similarities and the differences between these two concepts. The Comparative explanation is applied in the following systems: ITEM/PG, Lisp-Critic and C-book 2.1.4 Sorting Explanations This technique consists in sorting information which will be explained to the user. This information which is related to a same semantic concept, takes into account the user formation and his knowledge. This technique is implemented in Hypadapter and EPIAIM 2.2 Adaptive Navigation The idea of adaptive navigation techniques is to help the users to find their paths in hyperspace by adapting the style of link presentation to goals, knowledge and other characteristics of an individual user. The most popular techniques are: direct guidance, sorting links, hidden links and annotation links. 2.2.1 Direct Guidance It is the simplest technique of adaptive navigation support. Direct guidance consists in selecting the next best node or page for the user to visit according to the user s goal and other parameters represented in the user model. Among the systems which use this technique are Web Watcher, ISIS-Tutor, SHIVA and HyperTutor.

Modelling of an Adaptive Hypermedia System Based on Active Rules 151 2.2.2 Sorting Links This technique consists in sorting all the links of a particular page according to the criteria indicated in the user model. This sorting is decreasing according to the links importance. This technique is applied in the following systems: Anatom-Tutor, Hypadapter, Adaptive HyperMan, HYPERFLEX and WebWatcher. 2.2.3 Hidden Links The idea of hiding technique is to restrict the navigation space by hiding links to not relevant pages. This technique is easy to implement in the AHS. It avoids the user be lost in a large hyperspace. The systems which adopt this technique are: ISIS-Tutor, HyperTutor, SHIVA and WebWatcher. 2.2.4 Annotation Links Annotation links technique consists in augmenting the links that can tell the user more about the current state of the nodes behind the annotated links. These annotations can be provided in textual form or in the form of visual cues using. This technique is applied in the systems: Excel Handbook, Elm-art, Item/pg, ISIS-Tutor, Hypadapter. 3 Structure of an Adaptive Hypermedia System In this work, a novel tendency is adopted to build adaptive hypermedia systems. It consists in extending the traditional hypermedia systems towards the adaptive hypermedia systems using the adaptation techniques in the adaptive systems. We propose an adaptive hypermedia system which is based on active rules (Event- Condition-Action). More precisely, the specification of the components of this system, including the active rules, is based on the object concept. The advantage of active rules resides in the integration of all existing adaptation techniques in the system; it also allows easily introducing new adaptation strategies. The architecture of this system consists of three main parts: an adaptive subsystem, a traditional hypermedia subsystem and a tasks model (fig.1). 3.1 Adaptive Subsystem This part models the users characteristics and the semantic concepts that must be acquired by these users. It also selects the corresponding adaptation behaviour and organizes the events coming from the user. The adaptive subsystem contains the four following components: the user model, the semantic network model, the events analyser and the adaptive behaviour specification entity.

152 H. Raad and B. Causse Adaptive Subsystem TasksModel User Model Semantic Network Model Strategic Rules Events Analyser Adaptive Behaviour Specification Entity Hypermedia Subsystem Multimedias Resources Navigational Model Navigational Rules Interface Model Interface Rules Data flow link Associationlink User Fig. 1. Architecture of adaptive hypermedia system based on active rules 3.1.1 User Model In the user model, we adopted stereotypic approach at the granularity level. This approach accounts for the concept of group that allows classifying the users into categories. This approach, however, does not exclude the individual aspect of the user. This model consists of three main parts: The individual part focuses on the user s personal information. The common part represents the groups characteristics. The recovery part or the recovery model is devoted to represent the user s knowledge. This part is associated with the semantic concepts in the system. 3.1.2 Semantic Network Model It constitutes an organization of concepts and the relationships between these concepts. Each concept may have a set of attributes to represent its semantic aspects. The relationships determine the nature of the links between the concepts. This model represents the user s knowledge and identifies the navigational entities. 3.1.3 Events Analyser The events analyzer organizes the events coming from the user. This component feeds the user model by the events and sends the necessary events to the adaptive behaviour specification entity.

Modelling of an Adaptive Hypermedia System Based on Active Rules 153 3.1.4 Adaptive Behaviour Specification Entity This component determines the behaviour of the system by taking into account different users categories, the concepts. The adaptive behaviour specification entity selects and runs various rules bases: strategic bases, navigational bases and interface bases (to be explained later). This component respects the order in which the bases should be executed. 3.2 Hypermedia Subsystem This part is responsible for modelling the navigational aspect of the system. The hypermedia subsystem contains three components: a navigational model, an interface model, and the multimedia resources. 3.2.1 Navigational Model This model builds the navigational structures. It consists of two principal parts: the primitive elements like nodes and links; the navigational contexts which are based on the primitive elements. 3.2.2 Interface Model This model specifies the visible entities which are presented to final user. Each node in the navigational model is associated with a corresponding interface node. 3.2.3 Multimedia Resources (Database Multimedia) This part contains all the multimedia resources that can be used in the system as text, image, audio, and video. This component provides the navigational model by the necessary information while keeping the two parts clearly separated. 3.3 Tasks Model The behavior of the system is obtained by integrating the rules with a specific form: Event-Condition-Action; also called active rules. These rules are inspired from the production rules in the expert systems [Dayal et al, 88]. The active rules are applied in data bases domain to introduce an active aspect into these systems like HiPAC [Mccarthy & Dayal, 89] and ADACTIF [Tawbi, 96], but these rules are not largely used in the adaptive hypermedia domain. The importance of the active rules resides in the facility of composition of the system behavior. The logic of the active rules takes the following form: with occurrence of an event E, if a condition C is satisfied then the system will run an action A. A set of rules may compose a rules base. The base role is to run several elementary tasks which are coherent between them. In our system, we classified three categories of bases according to tasks type.

154 H. Raad and B. Causse 3.3.1 Strategic Rules This component represents a strategic view of the system. These bases determine the basic behavior of the system and select the navigational and interface bases. 3.3.2 Navigational Rules The navigational rules bases are devoted to specify the navigational behaviour. Each base selects the navigational context and suitable nodes and links. 3.3.3 Interface Rules This part is responsible to specify the interaction between the system and the user. Each interface node is associated with several interface rules bases. 3.4 Dynamic Model of Our System The goal of the dynamic model is to study the principal states of the system during its life cycle. This dynamic model is based on a method notation OMT. The following figure explains the various states of the life cycle in the system. Launch Events Interface Model Transmit Events Events Analyzer Select Interface Entities Sent Events Adaptive Behaviour Specification Entity Select Navigational space Send Navigational Model Request information Send information Request information information Select Interface Base Select Select Strategic Navigational Base Base Sent Events User Model Semantic Network Model Interface Rules Navigationel Rules Strategic Rules Fig. 2. Dynamic Model of adaptive hypermedia system The first event comes from the user who requests a set of goals to be realized. The interface model will be active to provide screens corresponding to the user. This one gives information depending on its goals. The interface model transforms this information into intern events and transmits it towards the events analyzer. This last composes and transmits the events towards the adaptive behaviour specification entity and the user model. The behavior specification entity will be active to select a strategic rules base by taking into account the user model and the semantic network model. According to the

Modelling of an Adaptive Hypermedia System Based on Active Rules 155 strategic base, the behavior specification entity selects navigational rules base, an interface entities and an interface rules base: According to these steps, the system provides an adaptive behavior to the user s needs. The user, in turn, reacts to start another set of events. 4 Evaluation of the System This system presents an excellent solution to extend an educational hypermedia system that conceived and implemented within project LINGUA. A simple example is given below to show how the rules bases specify the system behavior. Initially, a strategic base will be activated by an event Held_Aims_List (Fig. 3). This base makes up two lists of bases: Navigational_Base_List and Interface_Base_List and filter it by choosing the bases corresponding to the user. R1 : When Held_Aims_List If Value(Group.Domain)= Education et Value(Navigationnel_Base.Domain)= Education Then Add(Base current, Navigational_Base_List) R2 : When Held_Aims_List If Value(Group.Domain)= Education and Value(Interface_Base.Domain)= Education Then Add(Base current, Interface_Base_Liste) -- To select one or more navigational bases in the list Navigational_Base_List R3 : When Saturate(Navigational_Base_List) If Value(Group.Level)= Medium Then Select_Base(Navigational_Base_List) -- To select one or more interface bases in the list Interface_Base_List R4 : When Saturate(Interface_Base_List) If Value(Group.Level)= Medium Then Select_Base (Interface_Base_List) Fig. 3. Strategic base. After the strategic base selects a navigational base this one chooses the nodes and the navigational links based on the concepts and the semantic links in the semantic network model (fig 4). R1 : When Aim_Identified If Belong(Aim, Concept_List) Then Activate_Final_Point (Aim, Concept) R2 : When Identified_Final_Point(But) If Value(True) Then Find(Concepts_Known_List, User) and Add(Concepts_Known_List, Path) R3 : When Added(Concepts_Known_List, Path) If Nb_Member(Concepts_Known_List) > 0 Then Select_Links_Associated(Concepts_Known_List, Links_List) and Filter_List(Links_List, Educative_Links List) R4 : When Filtered_Educative_Links List If Nb_Member(Links_List) > 0 Then Find(Concept_Associed_Link, Links_List) and Add(Concept_Associed_Link, Path) Fig. 4. Navigational base. The strategic base also selects an interface node and a corresponding interface base. This one specifies the interaction scenario between the user and the system (fig 5).

156 H. Raad and B. Causse R1 : R2 : R3 : When Activated(Educative_Navigational_Node) If Belong(User, Group) Then Activate(Points_Bar) and Activate(Field.explication) and Activate(Button.Vocabulary) When Button_Clicked(Button.Video) If Value(User.Score_Point) > 10 Then Prevent(Annotation_Video) When Button_Clicked(Button.Video) If Value(User.Score_Point) < 10 Then Activate(Annotation_Video)) Fig. 5. Interface base. 5 Conclusion In this work, a novel AHS architecture model based fully on active rules (Event- Condition-Action) is presented. This model aims to facilitate the specification of the system adaptive behaviour. Based on the concept of active rules, this system applies all the adaptation techniques, which is not the case of the existing systems. For example, Anatom-Tutor and Adaptive HyperMan apply only two techniques sorting links and hidden links, ISIS-Tutor applies three techniques direct guidance, hidden links and annotation links. The separation between the behavioural part and the entities models makes it easy to add new adaptation techniques to our system. Moreover, the existence of three categories of rules bases supports the application of three adaptation types: adaptive presentation, adaptive navigation and strategic adaptation, whereas the existing systems don t. For example, EPIAIM and Lisp-Critic only offer adaptive presentation; HYPERFLEX and WebWatcher only offer adaptive navigation; Item/pg and Hypadapter jointly offer adaptive presentation and adaptive navigation. On another side, according to the comparison between our system and those of intelligent tutor, it was observed that the model navigational in our system offers the intelligent navigational behavior, whereas the intelligent tutor systems do not have this characteristic. This one allows our system to be integrated in the Internet network. References [Dayal et al, 88] [Debevc et al., 94] [Kaplan et al., 93] DAYAL U., BLAUSTEIN B. et BUCHMANN A.: The HiPAC Pro-ject: Combining Active Databases and Timing Constraints., SIGMOD RECORD, vol 17, no 1, pp 51-70, March 1988. DEBEVC M., RAJKO S. & DONLAGIC D.: Adaptive of Computing and Informatics, 18, pp 357-366, 1994. KAPLAN C., FENWICK J. & CHEN J.: Adaptive hypertext navigation based on user goals and context, User Models and User Adapted Interaction 3(3), pp 193-220, 1993.

Modelling of an Adaptive Hypermedia System Based on Active Rules 157 [Kaptelinin, 93] [Kay & Kummerfeld, 94] [Mccarthy & Dayal, 89] [Tawbi, 96] [Widom & Finkelstein, 90] KAPTELININ V.: Item recognition in menu selection: The effect of practice, INTERCHI 93 Adjunct Proceedings, Amsterdam, pp183-184, 1993. KAY J. & KUMMERFELD R. J.: An Individualised Course for the C Programming Language, Second Inter-national WWW Conference Mosiac and the Web, Chicago,IL, http://www.ncsa.uiuc.edu/sdg/it94/proceedings/educ/ kummerfeld/kummerfeld.html, 1994. MCCARTHY D.R. & DAYAL U.: The Architecture of an Active Data Base Management System, Proceeding ACM-Sigmod Conference Portland, pp 215-224, may 1989. TAWBI C.: ADACTIF : Extension d un SGBD à l Activité par une Approche Procédurale Basée sur les Rendez-vous, Thèse d université, Toulouse, 1996. WIDOM J. & FINKELSTEIN S.: A Syntax and Semantics for Set Oriented Production Rule in Relational Databases., Proceedings of SIGMOD, Atlantic City NJ, June 1990.