• Email: jlu at uwindsor
• Phone: 3786
• Office: Lambton Tower 5115

Course Overview

This course introduces theoretical and practical aspects of both the current web and the semantic web. Topics will include web characteristics, web graph and analytics, techniques in building a search engine inluding crawling, page ranking, and latent semantic indexing. We will also cover web ontology.

Time and Place

• Lecture time and place: Tuesday and Thursday 10:00-11:20 CE 2104.
• Office hours: Tuesday/Thursday 11:30-12:30.

Schedule for final project presentation

Note that each presentation should be 15 minutes long, and there will be 5 minutes for questioning and answering.

Each group should submit a final project report containing no more than 1000 words no later than December 15. A web site should also be available by December 15 for more details of the project including a live demo.

Nov 26
1. group 5: Nwokeoji , Nnamdi Kingsley web site
2. group 6: Reid , James H. and Willis , Jordan T. Web site
3. group 7: Sun , Xu and Zheng , Shaochen. web site
4. group 8: Wu , Jiayi and Zhang , Yi. web site

Nov 28

1. group 1: Agboola , Adewale Taiwo and Chachad , Amrutraj. web site
2. group 2: Cao , Xiao Ni and Cui , Xiutian. web site
3. group 3: Chittle , Joshua David and Donais , Jonathan Alexander web site
4. group 4: Gherani , Mohit and Sumon , Mahmud Hossan. web site

Tentative content of the course includes:

• Week 1: Course outline (pdf ), Introduction (slides in pdf)
• Week 2,3,4: Lecture slides: Web search (Web search basics webchar.pptx, Near duplicate, Link analysis and spam, web crawling)
  • Matlab program for graph example graphExample.m
  • Plotting power law distribution powerLawPlot.m
  • Illustration of PageRank algorithm in Matlab pagerank.m
  • Readings: Chapter 5 of MMD, Chapter 19, 20, and 21 of IR, and the papers in the following table.

    topic	Papers		Time
    Crawler tutorial		Mahmud Sumon, Mohit Gherani	Oct 15
    Pagerank algorithm tutorial	IR, MMD and Page, Lawrence; Brin, Sergey; Motwani, Rajeev and Winograd, Terry (1999). The PageRank citation ranking: Bringing order to the Web.	Xiutian Cui, Xiaoni Cao	Oct 15
    Near duplicate detection	MMD, Detect near duplicates, Jaccard similarity, Chapter 3	Yi Zhang, Jiayi Wu	Oct 15
    Search Engine tutorial	Lucene Lucene in Action	Shaochen Zheng, Sun Xu	Oct 15
    Clustering Coefficient	The power of wedge sampling, MMD, Clustering Coeeficient, Triangles, Chapter 10
    Search engines	IR and Steve Lawrence, C. Lee Giles, Searching the WWW , Science 1998. Steve Lawrence; C. Lee Giles (1999). "Accessibility of information on the web". Nature 400 (6740): 107.
    Web as graph	R Albert, H Jeong, AL Barabasi - 1999, Diameter of the World Wide Web. , Nature 1999. M., Kumar, et al.. The web as a graph. Donato, D., Laura, L., Leonardi, S., and Millozzi, S. 2007. The Web as a graph: How far we are. ACM Trans. Internet Technol. 7, 1 (Feb. 2007), 4.	Adewale Agboola, Amrut Chachad	Oct 15

• Week 6,7,8,9: Lecture slides: Ontology, RDF, RDFS, OWL. RDF query .
• Lucene :
  • Use Lucene to build a search engine.
  • Lecture slides
  • A good Lucene tutorial site. There are also sample code.
  • Lucene in Action book.
  • A java program to index DBLP data (DBLP.java). Since dblp.xml file is rather large (~879MB), SAX XML parser rather than DOM parser is used.
  • DBPedia

• Readings : Chapters 1-5, SW.

  Topic	Papers		Time
  A vision of semantic web	Tim Berners-Lee, James Hendler and Ora Lassila, The Semantic Web, A new form of Web content that is meaningful to computers will unleash a revolution of new possibilities, Scientific American, May 2001
  DBPedia	DBpedia: A Nucleus for a Web of Open Data, ren Auer, Christian Bizer, Georgi Kobilarov, Jens Lehmann, Richard Cyganiak and Zachary Ives, The Semantic Web,722--735,2007, Springer Slides	Joshua Chittle, John Donais	Oct 17
  Social Web	M Gjoka et al., A walk in facebook:uniform sampling of users in online social networks
  Ontology matching	Doan, A., Madhavan, J., Domingos, P., and Halevy, A. 2002. Learning to map between ontologies on the semantic web. In Proceedings of the 11th international Conference on World Wide Web (Honolulu, Hawaii, USA, May 07 - 11, 2002). WWW '02. 662-673.	James, Jordan	Oct 15

Week 10, 11,12: Lecture slides: Matrix decomposition and latent semantic indexing. slides by Jure Leskovec , LSI slides (pdf) , Graph sampling slides (pdf) .

Week 13: Project presentation and evaluation

Ontology Data

The following table lists some ontologies and their corresponding graphs.

Ontology	graph txt file	graph
1. SUMO.owl (323KB)	sumoSubclass.txt(~700 edges)	subclass fdp layout
2. All the relatestion extracted using jena. The java program	sumoAll.txt(~2700 edges)	sumoAll fdp layout, circle layout, twopi layout
3. dbpedia.owl(~700KB)	graph txt
4. SUMO2.owl(~30MB)	graphviz txt	twopi layout(79MB) , a 3D fig produced by Wang Hao
5. SUMO2 subclass (5000 edges)	graphviz txt	fdp fig , dot fig , twopi fig ,
6. SUMO2 subclass & domain range(7000 edges)	graphviz txt	fdp fig , dot fig , twopi fig ,
7. SUMO2 domain range (1700 edges)	graphviz txt	fdp fig , dot fig , twopi fig ,
8. SUMO2 classes	graphviz txt	fdp fig , dot fig , twopi fig ,

The semantic web data are extracted from various sources. For DBPeida data, here is a sample java program to construct a graph from SUMO2 (~30MB) ontology. The output is a txt file depicting the graph in graphviz format.

The graph is then drawn using graphviz. Grapphviz can create several different layouts from a graph definition. One layout is called fdp, which uses the spring model so that nodes having stronger connections are put closer on the canvas. The fdp layout reault is here . Graphviz can be downloaded here. The command to run graphviz is here. It also shows how to generate the different layouts.

Reference books