In this chapter, a conceptual model is presented that shows how the proposed notion of tag-based customisation fits and extends the present tagging model in the Web domain. Section 3.1 outlines the extended tagging model based on the triples model (see Figure 1). Section 3.2 presents and elaborates on the interaction customisation model adopted from the literature.
3.1 EXTENDED TAGGING MODEL
The characteristics of tags, particularly personal and contextual appear suitable to afford customised interactions, unique to every individual based on tags assigned to resources. This notion is simply referred to as tag-based customisation. The ability to represent resources in user’s own keywords presents the opportunity to interact and carry out website features through tags which also extends the present understanding and use of tags beyond information management (see Figure 6). Figure 6 depicts the existence of a tagging system in the form of the aforementioned triples model (see Figure 1) in a Web domain such as social bookmarking or finance. This facilitates the well researched and understood notion of information management made possible via tags. However, tags can in turn facilitate tag-based customisation as an alternative or extension to the present Web interaction afforded by standard HTML objects such as dropdown boxes, menus, tables, etc.
The process of tag-based customisation shown in Figure 6 is illustrated in Figure 7.
Figure 6 depicts the use of tags as input for the interaction process and consequently the tag-based customisation model produces the output that enables quick and easy access of website features through customisation. In other words, the customisation makes it possible for users to interact with a particular website just by using tags. Thus, website features are customised to individual
Figure 6 Extended tagging model Information management
users through the model, which in turn minimize effort and alleviate the need for users to recognize and decide the appropriate features to fulfil their goals or needs.
The tag-based customisation process shown in Figure 7 is useful to ease and simplify interaction in a Web domain. This thesis proposes that this can positively impact usability of existing websites, particularly in terms of satisfaction, efficiency and effectiveness. The customisation model is independent of domain or website features hence it may be applied to a wide range of domains. However, for the purpose of this study, the model is applied and evaluated in a specific E-commerce domain – online and mobile banking. The tag-based customisation model provides the knowledge and understanding to extend and support the use of tags as a means of customised interaction over the Web with the goal of positively affecting usability. The different types of customised interaction types are outlined below.
3.2 INTERACTION CUSTOMISATION
This thesis explores customisation through user-defined tags based on the interaction customisation model conceptualised by Fung (2008) for his work on banking customisation. The customisation model comprises of three distinct customisation types derived from the levels-of-processing framework (F. I. M. Craik et al., 1972). The levels-of-levels-of-processing framework offers an approach to process messages in the human-computer interaction context. The processing is divided into three levels and each level signifies a particular type of qualitative processing carried out on a message (F. Craik, 2002). These three levels of processing vary from simple (shallow) to complex (deep), and the move from one level to another marks change of processing qualitatively. The sequence of processing is not linear rather each level exists separately from the other. As such each level of processing represents a specific kind of expansion on the message (F.
Craik, 2002).
The following section presents the three types of customisation. They are known as remembering, comprehension and associative. Important characteristics of these customisation
Figure 7 Tag-based customisation process
types include non-sequential processing, unique ways of interpreting users’ knowledge and attitudes, and non-dependant qualitative processing (Fung, 2008). Below are the customisation types conceptualised based on adaption and modification of the levels-of-processing framework.
3.2.1 Remembrance-based
This customisation type is derived from cognitive processing which uses recognition to process messages during interaction. This type of processing, in the communication context for example, simply needs an individual to recognise and acknowledge the presence of the incoming message, without any other form of elaboration (Fung, 2008).
The first customization type, labelled as remembrance-based, refers to a website that is customised for users based on simple remembrance of user’s information gathered during registration or based on the recurrence rate of a particular action on a website (e.g., most-frequently used website feature) without the website necessarily understanding the meaning of the information. For instance, a website keeping track of user visits to a page and consequently, customising the front page of the website to the most frequently visited page for subsequent user visits is an implementation of remembrance-based customisation.
This customisation is visible with MyYahoo.com where based on the user’s information provided at the time of registration, the Web content is customised in the form of personal greeting and content tailoring according to the user’s interests and location. The user information is stored in a database as it is without any other processing and retrieved when required.
3.2.2 Comprehension-based
This customisation type is derived from cognitive processing that uses analysis to process messages during interaction. This type of processing takes places when an individual assigns meaning to the incoming message through analytical elaboration (Fung, 2008). Through analysis, an individual grips the underlying idea being passed on through the message. In a social interaction context, when someone in an air-conditioned meeting room says, “I am feeling very cold” then immediately other individuals in the room discover the notion behind and assign the meaning that the air-condition needs to be turned off, for instance.
The second customisation type, simply known as comprehension-based, refers to a website that recognises user’s behaviours by assigning meanings and contingent attempts to provide assistance towards fulfilling the user’s needs. The facility to identify user’s behaviours as part of a procedure on a website and to subsequently comprehend the meaning of that behaviour
through analytical elaboration is a clear application of comprehension type customisation (Fung, 2008).
An illustration of this customisation is MS Office’s ‘Office Assistant’, where the program based on a user’s typing behaviour attempts to provide assistance directed at satisfying the user’s needs. For example, typing the phrase “Dear” and hitting enter triggers the Office Assistant where a pop up is shown asking whether the user requires help to write the letter. If the user clicks the “yes” button, a letter wizard will be shown to guide the user. As a result of analysing the typing behaviour (e.g., the word “Dear”) and discovering the underlying meaning as letter writing, the feature is customised to ease the task of letter writing.
3.2.3 Association-based
This customisation type is derived from cognitive processing that uses reflection to process messages during interaction. This type of processing is considered deep and occurs when an individual forms an association on the incoming message through reflective elaboration (Fung, 2008). Essentially, an individual looks for similarities in the message content and semantics stored in his/her memory. Using this as a basis, the individual then develops an associative link between the message content and stored semantics allowing for reflection on the implication of the message.
The last type of customization, referred to as association-based, refers to a website that provides customisation through association of a user’s behaviour with other individuals who have similar behaviours to reflect on the similar needs the user might have in common. The website attempts to locate similar behaviours from a database to match a specific user’s behaviour in order to provide associative customisation (Fung, 2008).
A simple and straightforward example is Amazon.com’s personal recommendation where a list of books purchased by other users is displayed along with the search result for a book requested by a user. Comparing and contrasting a particular user’s search behaviour to all other users’ search behaviours in the database achieve this. Amazon.com forms an association by reflecting on a user’s searching behaviour to other like-minded people’s search behaviours captured in a database.
3.3 SUMMARY
This chapter presented a conceptual model that extends the present tagging model found in the literature to support the notion of tag-based customisation. To facilitate this course, a
customisation model from the literature is adopted, which has been applied in the banking context in previous studies.
In the forthcoming chapters of the thesis, the application of tags to facilitate each of the above mentioned customisation types are discussed. The proposed tag-based approach is explicit and both user- and system- based. The user initiates the customisation process implicitly via tags and the system performs the customisation based on the tags assigned. Examples of each types of customisation are provided in the Preliminary Work chapter (Chapter 5). A detailed explanation of the tag-based approach in other E-commerce domains for two other contexts (retail and travel), using online and mobile banking as a reference is presented in the Customisation Model chapter (Chapter 8).