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Information
| Code | CENG0023 |
| Name | Algorithms for Web Data Analysis |
| Semester | . Semester |
| Duration (T+A) | 3-0 (T-A) (17 Week) |
| ECTS | 6 ECTS |
| National Credit | 3 National Credit |
| Teaching Language | İngilizce |
| Level | Doktora Dersi |
| Type | Normal |
| Mode of study | Yüz Yüze Öğretim |
| Catalog Information Coordinator |
Course Goal
The aim of this course is to design and analyze algorithms for processing data on the Web.
Course Content
The course covers algorithms including information retrieval and web search, pagerank, hits, mapreduce, crawling algorithms, structured data extraction, information integration, and web usage mining.
Course Precondition
As prerequisite of this course the instructor expects that the students have strong algorithm design, analysis, and implementation background.
Resources
Bing Liu, “Web Data Mining: Exploring Hyperlinks, Contents, and Usage Data”, Second Edition, July 2011.
Notes
Recent papers about the course content
Course Learning Outcomes
| Order | Course Learning Outcomes |
|---|---|
| LO01 | Identifies algorithms that can be used for web data analysis. |
| LO02 | Explains recent developments about Web data analysis. |
| LO03 | To be able to analyze algorithms for processing data on the Web. |
| LO04 | To be able to apply algorithms for processing data on the Web. |
Relation with Program Learning Outcome
| Order | Type | Program Learning Outcomes | Level |
|---|---|---|---|
| PLO01 | Bilgi - Kuramsal, Olgusal | On the basis of the competencies gained at the undergraduate level, it has an advanced level of knowledge and understanding that provides the basis for original studies in the field of Computer Engineering. | 3 |
| PLO02 | Bilgi - Kuramsal, Olgusal | By reaching scientific knowledge in the field of engineering, he/she reaches the knowledge in depth and depth, evaluates, interprets and applies the information. | 3 |
| PLO03 | Yetkinlikler - Öğrenme Yetkinliği | Being aware of the new and developing practices of his / her profession and examining and learning when necessary. | 4 |
| PLO04 | Yetkinlikler - Öğrenme Yetkinliği | Constructs engineering problems, develops methods to solve them and applies innovative methods in solutions. | |
| PLO05 | Yetkinlikler - Öğrenme Yetkinliği | Designs and applies analytical, modeling and experimental based researches, analyzes and interprets complex situations encountered in this process. | 2 |
| PLO06 | Yetkinlikler - Öğrenme Yetkinliği | Develops new and / or original ideas and methods, develops innovative solutions in system, part or process design. | |
| PLO07 | Beceriler - Bilişsel, Uygulamalı | Has the skills of learning. | |
| PLO08 | Beceriler - Bilişsel, Uygulamalı | Being aware of new and emerging applications of Computer Engineering examines and learns them if necessary. | 3 |
| PLO09 | Beceriler - Bilişsel, Uygulamalı | Transmits the processes and results of their studies in written or oral form in the national and international environments outside or outside the field of Computer Engineering. | 1 |
| PLO10 | Beceriler - Bilişsel, Uygulamalı | Has comprehensive knowledge about current techniques and methods and their limitations in Computer Engineering. | 2 |
| PLO11 | Beceriler - Bilişsel, Uygulamalı | Uses information and communication technologies at an advanced level interactively with computer software required by Computer Engineering. | 3 |
| PLO12 | Bilgi - Kuramsal, Olgusal | Observes social, scientific and ethical values in all professional activities. |
Week Plan
| Week | Topic | Preparation | Methods |
|---|---|---|---|
| 1 | Introduction to information retrieval systems | Reading the lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 2 | Structure of Web search engines | Reading the lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 3 | Pagerank and hits algorithms | Reading the lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 4 | Mapreduce algorithm and its applications | Reading the lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 5 | Web crawling algorithms | Reading the lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 6 | Structured data extraction algorithms | Reading the lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 7 | Data integration algorithms | Reading the lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 8 | Mid-Term Exam | Reading the lecture notes | Ölçme Yöntemleri: Ödev |
| 9 | Web usage mining | Reading the lecture notes | Öğretim Yöntemleri: Anlatım, Tartışma |
| 10 | Opinion mining | Literature survey, preparing presentation | Öğretim Yöntemleri: Örnek Olay, Soru-Cevap |
| 11 | Sentiment analysis | Literature survey, preparing presentation | Öğretim Yöntemleri: Örnek Olay, Soru-Cevap |
| 12 | Social network analysis | Literature survey, preparing presentation | Öğretim Yöntemleri: Örnek Olay, Soru-Cevap |
| 13 | Focused crawling | Literature survey, preparing presentation | Öğretim Yöntemleri: Örnek Olay, Soru-Cevap |
| 14 | Crawler ethics and conflict resolution | Literature survey, preparing presentation | Öğretim Yöntemleri: Örnek Olay, Soru-Cevap |
| 15 | Project presentation | Coding of the selected algorithm, experimental analysis | Öğretim Yöntemleri: Proje Temelli Öğrenme |
| 16 | Writing the project report | Preparing the project report | Ölçme Yöntemleri: Proje / Tasarım, Sözlü Sınav |
| 17 | Term Exams | Preparing the project report | Ölçme Yöntemleri: Proje / Tasarım, Sözlü Sınav |
Student Workload - ECTS
| Works | Number | Time (Hour) | Workload (Hour) |
|---|---|---|---|
| Course Related Works | |||
| Class Time (Exam weeks are excluded) | 14 | 3 | 42 |
| Out of Class Study (Preliminary Work, Practice) | 14 | 5 | 70 |
| Assesment Related Works | |||
| Homeworks, Projects, Others | 0 | 0 | 0 |
| Mid-term Exams (Written, Oral, etc.) | 1 | 15 | 15 |
| Final Exam | 1 | 30 | 30 |
| Total Workload (Hour) | 157 | ||
| Total Workload / 25 (h) | 6,28 | ||
| ECTS | 6 ECTS | ||