460-4059/01 – Adaptive Web Systems (AWS)
Gurantor department | Department of Computer Science | Credits | 4 |
Subject guarantor | doc. RNDr. Petr Šaloun, Ph.D. | Subject version guarantor | doc. RNDr. Petr Šaloun, Ph.D. |
Study level | undergraduate or graduate | Requirement | Optional |
Year | 2 | Semester | summer |
| | Study language | Czech |
Year of introduction | 2013/2014 | Year of cancellation | 2022/2023 |
Intended for the faculties | FEI | Intended for study types | Follow-up Master |
Subject aims expressed by acquired skills and competences
To learn the principles and technologies of adaptive semantic web, and virtually test / create content, annotations, or implement algorithms or techniques for personalization and adaptation in the environment of adaptive system, implementation in Java and C #.
Teaching methods
Lectures
Tutorials
Summary
Semantic web enables to offer content targeted to the user's interests and profile. Such a personalization performs adaptive web systems using domain model, user model, technology of adaptation and possibly collaborative recommendation based on social recommendation. For these approaches are appropriate technologies, techniques and metrics. The overview at the appropriate level will be part of the course. The practical part will be partly devoted to work with a functional prototype of a web XAPOS adaptive system, where students will perform the appropriate task.
Compulsory literature:
Brusilovski, P., Kobsa, A., Nejdl, W., The Adaptive Web: Methods and Strategies of Web Personalization, Springer 2007
Recommended literature:
Bing, L., Web data mining, Springer 2007
Mendes, E., Mosley, N., Web Engineering, Springer 2007
Way of continuous check of knowledge in the course of semester
Presentation on a given theme.
Individual homework.
E-learning
Other requirements
There are no extra knowledge necessary.
Prerequisities
Subject has no prerequisities.
Co-requisities
Subject has no co-requisities.
Subject syllabus:
Lectures:
1st Introduction to the adaptive Web.
2nd Models, modeling and basic concepts.
3rd Link analysis, static and dynamic algorithms evaluation sites.
4th User model in adaptive web-based systems and adaptive learning systems.
5th User profile and personalize.
6th Data collection and preprocessing of texts in natural language.
7th Data Mining for personalization site.
8th Documents modeling.
9th Personalization and Web search.
10th Adaptive navigation.
11th Filtering and referral systems.
12th Recommending content-based and event-based recommendation.
13th Adaptive presentation of web content.
Exercises:
The aim of the exercise is practical work with a functional prototype of adaptive web system XAPOS. Specifically, the transformation of inputs and outputs to/from the internal format of XAPOS, working with ontologies using tools for language OWL (Protege for example). Analysis and adjustment module XAPOS, which is available in source form arg.vsb.cz/XAPOS/
Conditions for subject completion
Occurrence in study plans
Occurrence in special blocks
Assessment of instruction