Fine-Grained Adaptive User Interface for Personalization of a Word Processor: Principles and a Preliminary Study

Dostál, Martin; Eichler, Zdenek

doi:10.1007/978-3-642-22098-2_99

Cited by 7 publications

(4 citation statements)

References 10 publications

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“…In qualitative measures, users were able to select their desired commands in cases of toolbars, menus and boulevard during first attempt around 62.7 percent, 53.3 percent and 66.4 percent respectively. But users failed to select command during 30 seconds (maximum time) in 20 cases for toolbar, 67 cases for menus and 11 cases for boulevard part of experiment [27]. In 1999, Dey et al stated that context can be used to define the position of an entity.…”

Section: Literature Reviewmentioning

confidence: 99%

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User Context Ontology for Adaptive Mobile-Phone Interfaces

Iqbal

Nickabadi²,

Shahzad

et al. 2021

IEEE Access

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The Adaptive User Interface (AUI) adapts to the changes in the context of use and provides improved interaction abilities for different users. The adaptivity in the user interfaces requires in depth knowledge of context. There is a need to enrich user profiles to achieve the personalized services with the ability to adapt the user's context. The context can be reflected in a particular kind of knowledge and hence modeled as ontology. Ontology based context models are effective means to handle complex situations that support the sharing or integration of context information. This paper presents ontology based context model using OWL for adaptive mobile devices. It models the context over its four major elements including device, user, environment (location and time) and activity. The proposed ontology was derived in different classes, relationships, associations, dependencies and constraints to model dynamic context. Ontologies present a standardized, consistent and shareable context model. The context model and consequent context snapshots can be acknowledged by AUI to present a suitable user interface. The ontology was developed using Protégé on the basis of each context type having different values. Semantic querying (SPARQL) was used for knowledge acquisition. Moreover, the Pellet and HermiT Reasoner were used to verify the rules, relations and constraints to avoid the inconsistency between classes. Comparative to other context models for adaptive interfaces, ontological model provides more of scalability and growth with learning new context in to the shared context knowledge.

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Section: Literature Reviewmentioning

confidence: 99%

“…It is very difficult to collect relevant information about the causes of usability hindrance from users. This issue may create difficulties for application developers to develop adaptive applications according to user's contextual information [27].…”

Section: A User Context and Usage Environmentmentioning

confidence: 99%

User Context Ontology for Adaptive Mobile-Phone Interfaces

Iqbal

Nickabadi²,

Shahzad

et al. 2021

IEEE Access

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“…At home and abroad, has been carried out for reconfigurable system research includes hardware based on chip technology of reconfigurable computing, in response to the reconfigurable manufacturing of market demand changes, oriented programmable wireless communication technology and software engineering of reconfigurable software design, etc. [7][8][9][10][11][12].…”

Section: Introductionmentioning

confidence: 99%

Research of Network System Reconfigurable Model Based on the Finite State Automation

Zhou

Chang

2014

JNW

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Since the network analysis model based on the system state exists the issues of network survivability safety, fault tolerance and dynamic ability are adapted to the environment changes, in this paper, network system model based on the finite state automation has reconfigurable quality. The model first puts forward the concept of reconfigurable network systems and reveals its robustness, evolution and the basic attributes of survivability. By establishing a hierarchical model of system state, the system robust behavior, evolution behavior and survival behavior are described. Secondly, network topology reconfigurable measurement as an example, puts forward the quantitative reconfigurable metrics. At last, the example verification. Experiments show that the proposed reconfigurable quantitative indicators of reconfigurable resistance model for [1.391, 1.140, 1.591] prove that the network is an efficient reconfigurable network topology, which can effectively adapt the dynamic changes in the environment.

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“…That may bring great influence and loss to the human being [1] ．Therefore, it becomes the focus of attention to build a strain of reconfigurable network system [2] . It is required to construct the network system of reconfigurable resistance, can be efficient allocation of resources available for quick response and adapt to the change [3] ．The mainly challenge for building reconfigurable network system is to take many dynamic characteristic into account [4] .Some researches discussed the hardware technology, such as reconfigurable computing, reconfigurable manufacturing and so on [5] . The software engineering and telecom technology are also studied in past research [6] .…”

Section: Introductionmentioning

confidence: 99%

Research on Reconfigurable Network Model with Finite State Analysis

Zhou

Chang

2014

AMM

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The paper aims to develop an updated network system reconfigurable model based on the Finite State Automation. Firstly, the paper reviews the concept of reconfigurable network systems and reveals its robustness, evolution and the basic attributes of survivability.Then the system robust behavior, evolution behavior and survival behavior are described with a hierarchical model. Secondly, the study builds the quantitative reconfigurable metric with network topology reconfigurable measurement example. Finally, the result of experiments shows that the proposed reconfigurable quantitative indicator of reconfigurable resistance model suggests that the network is an efficient reconfigurable network topology, which can effectively adapt the dynamic changes in the environment.

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Fine-Grained Adaptive User Interface for Personalization of a Word Processor: Principles and a Preliminary Study

Cited by 7 publications

References 10 publications

User Context Ontology for Adaptive Mobile-Phone Interfaces

User Context Ontology for Adaptive Mobile-Phone Interfaces

Research of Network System Reconfigurable Model Based on the Finite State Automation

Research on Reconfigurable Network Model with Finite State Analysis

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