Topics for Projects and Thesis @IWM/KC

Contact: Andreas S. Rath (arath@know-center.at), Didier Devaurs (ddevaurs@know-center.at)

The topic “Online Task Detection” belongs to the research field of User Context Detection. The term “user context” is used to describe a user’s computational environment (e.g. user interactions, current task, recently opened documents, work environment). User context is described in formal “user context models” and may be utilized for task recognition, context-based information retrieval or context-aware applications.
For a Bachelor or Master Thesis or Project in the field of User Context Detection, you need basic programming skills and interest for the following fields

For a Bachelor or Master Thesis or Project in the field of User Context Detection, you need basic programming skills and interest for the following fields

Human Computer Interaction, Personal Information Management, Semantic Technologies, Machine Learning and Context-Aware Information Retrieval

Short description of the project “Online Task Detection”

• A task is a piece of work that needs to be done by a user. User context observation mechanism can capture those parts of the task execution that involve interactions with the user’s computer desktop, applications and resources. Based on these observations task detection should detect which task is currently performed by the user.
• Detecting the task a user is performing at the moment is challenging because the user can utilize multiple resources or can switch between various tasks (multi-tasking).
• The goal of the project is to find and implement algorithms that can detect which parts of the observed user context belong to the same task. The evaluation of the algorithms can be done on existing user context datasets and should be implemented into an already existing prototype that is based on Java and Eclipse RCP.

For an overview of all topics related to User Context Detection see User Context Detection - Themen SS 2009

Contact:  Didier Devaurs (ddevaurs@know-center.at), Andreas S. Rath (arath@know-center.at)

The topic “User-oriented Task Detection” belongs to the research field of User Context Detection. The term “user context” is used to describe a user’s computational environment (e.g. user interactions, current task, recently opened documents, work environment). User context is described in formal “user context models” and may be utilized for task recognition, context-based information retrieval or context-aware applications.
For a Bachelor or Master Thesis or Project in the field of User Context Detection, you need basic programming skills and interest for the following fields

For a Bachelor or Master Thesis or Project in the field of User Context Detection, you need basic programming skills and interest for the following fields

Human Computer Interaction, Personal Information Management, Semantic Technologies, Machine Learning and Context-Aware Information Retrieval

Short description of the project “User-oriented Task Detection”

• A task is a piece of work that needs to be done by a user. User context observation mechanism can capture those parts of the task execution that involve interactions with the user’s computer desktop, applications and resources. Based on these observations task detection should detect which task is currently performed by the user.
• The notification of a user that a new task has been detected may interrupt the user’s work, such that is important to reduce false and too often notification.
• The goal of the project is to study “when” and “how” a task should be detected and presented to the user for confirming or refining the detection result. The gathered insight should be implemented into an already existing prototype that is based on Java and Eclipse RCP.

For an overview of all topics related to User Context Detection see User Context Detection - Themen SS 2009

Contact: Didier Devaurs (ddevaurs@know-center.at), Andreas S. Rath (arath@know-center.at)

The topic “Context Detection in Web Browsers” belongs to the research field of User Context Detection. The term “user context” is used to describe a user’s computational environment (e.g. user interactions, current task, recently opened documents, work environment). User context is described in formal “user context models” and may be utilized for task recognition, context-based information retrieval or context-aware applications.
For a Bachelor or Master Thesis or Project in the field of User Context Detection, you need basic programming skills and interest for the following fields

For a Bachelor or Master Thesis or Project in the field of User Context Detection, you need basic programming skills and interest for the following fields

Human Computer Interaction, Personal Information Management, Semantic Technologies, Machine Learning and Context-Aware Information Retrieval

Short description of the project “Context Detection in Web Browsers”

• The web browser has become a key application on nowadays desktop computers which is used for various types of tasks. Hence it would be interesting to observe how users utilize the browser and how they interact with it when they perform their tasks.
• Since it is tedious and time consuming for the users to manually have enter and describe what they are doing it is a necessity to develop mechanisms that are able to automatically collect context data about the users.
• The goal of this project is analyze what kind of user context information can automatically be collected in a web browser and to develop plug-ins for web browsers to do so. User context data can be but is not limited to the currently viewed web page, mouse movements, text and mouse inputs, text highlighting, text modifications, page content that is currently in focus, bookmarking, reloading a webpage, forward and backward navigation, printing, using the search box or copy & cut & paste interactions.

For an overview of all topics related to User Context Detection see User Context Detection - Themen SS 2009

Contact:Viktoria Pammer (vpammer@know-center.at)

The topic “Assessment of description logic inferences of an ontology modelled in a Semantic MediaWiki” belongs to the research field of Modelling and Model Evaluation. Here, with the term Model, we refer to an ontology. The purpose of an ontology in computer science is to formally and unambiguously describe the relevant notions of a domain. People constructing an ontology need to be supported by design methodologies, tools and methods to create and evaluate their ontologies.

For a Bachelor or Master Thesis or Project in the field of Modelling and Model Evaluation, you need basic programming skills and interest for the following fields

Knowledge representation formalisms (description logics/OWL-DL), Semantic technologies, Knowledge elicitation techniques, and Cognitive theories

Short description of the project “Assessment of description logic inferences of an ontology modelled in a Semantic MediaWiki”

• For a human user, automatic inferences are often not obvious. Manually modelled statements lead to unwanted entailed statements.
• In the MoKi, an extension to the Semantic MediaWiki, users model an ontology in a rather informal (wiki) way.
• The informal model is automatically, using some rules of thumb, translated into a formal mode.
• Goal of the project: Consequences of the translation need to assessed by the user, and removed if necessary.

For an overview of all topics related to Modelling and Model Evaluation see

Modelling and Model Evaluation - Themen SS 2009

Contact:Viktoria Pammer (vpammer@know-center.at), Barbara Kump (bkump@tugraz.at)

The topic “Evaluation of automatically generated prerequisite relation” belongs to the research field of Modelling and Model Evaluation. Here, with the term Model, we refer to an ontology.

The purpose of an ontology in computer science is to formally and unambiguously describe the relevant notions of a domain. People constructing an ontology need to be supported by design methodologies, tools and methods to create and evaluate their ontologies.

For a Bachelor or Master Thesis or Project in the field of Modelling and Model Evaluation, you need basic programming skills and interest for the following fields

Knowledge representation formalisms (description logics/OWL-DL), Semantic technologies, Knowledge elicitation techniques, and Cognitive theories

Short description of the project “Evaluation of automatically generated prerequisite relation”

• In the case of the skill model, prerequisite relations between skills are implicit in the mappings from tasks to required skills
• For a human user, automatic inferences are often not obvious. Manually modelled statements lead to unwanted entailed statements.
• Goal of the project: Modifications of the explicit statements (prerequisite relation between skills) shall be reflected in the original structure (skill model)

For an overview of all topics related to Modelling and Model Evaluation see
Modelling and Model Evaluation - Themen SS 2009

Contact:Viktoria Pammer (vpammer@know-center.at), Barbara Kump (bkump@tugraz.at)

The topic “Ontology Questionnaire: Evaluation of Skill Model in APOSDLE with respect to its semantics” belongs to the research field of Modelling and Model Evaluation. Here, with the term Model, we refer to an ontology.

The purpose of an ontology in computer science is to formally and unambiguously describe the relevant notions of a domain. People constructing an ontology need to be supported by design methodologies, tools and methods to create and evaluate their ontologies.

For a Bachelor or Master Thesis or Project in the field of Modelling and Model Evaluation, you need basic programming skills and interest for the following fields

Knowledge representation formalisms (description logics/OWL-DL), Semantic technologies, Knowledge elicitation techniques, and Cognitive theories

Short description of the project “Ontology Questionnaire: Evaluation of the Skill Model in APOSDLE with respect to its semantics”

• Skill Model: A task is assigned a number of skills (hierarchy) which are required to perform the task
• The task-skill assignment needs to be evaluated
• Currently this evaluation requires the manual creation of a questionnaire
• Goal of the project: Automated creation of the questionnaire and automated correction of the skill model in dependence of the answer

For an overview of all topics related to Modelling and Model Evaluation see
Modelling and Model Evaluation - Themen SS 2009