Information and Web Communication Science
A.Y. 2019/2020
Learning objectives
The understanding and usage of the techniques and tools that determine the visibility of web content is a cross-cutting and pervasive theme within the world of Information and Communication Technology (ICT). It is of interest not only to its professionals within the discipline, but also to communication experts and humanist scholars in general. The first unit provides basic ideas on the structure of the web, search engines and techniques for finding information. The second unit discusses techniques for improving the visibility of content published on the web, more commonly known as Search Engine Optimization (SEO) techniques. Beyond this the final unit presents the emerging theme of the "data web", describing its main features and differences with respect to the model traditionally known as the "information web" and ultimately providing the necessary knowledge to assess the impact that these new tools have on conventional SEO techniques.
Expected learning outcomes
The student will need to have an adequate measure of Knowledge and Skills.
Knowledge: The student should possess knowledge relative to the retrieval of information on the internet with a particular emphasis on search engines and related techniques for word-processing, indexing and query processing. They will be able to describe the characteristics of the main models of repair (boolean vs. vector) and techniques to evaluate the effectiveness of recollection within the metrics of precision, recall and f-measurement. In addition, the student will need to have knowledge regarding the visibility of sites in terms of search engine availability (the so-called SEO - Search Engine Optimization). To do this, the student will need to know the main constructs of HTML5 language, link analysis techniques, as well as the definition of "data web", the various types of microdata and the impact that these ideas have on both on-site and off-site SEO techniques.
Skills: The student will acquire the following skills:
· distinguish the characteristics and application scopes of the Boolean recollection model from the vector model;
· know how to apply the techniques of text transformation, indexing and query processing of an information recollection system;
· know how to apply TF-IDF-based vector-based reperitable measurement techniques;
· know how to apply the evaluation techniques of an information recollection system based on precision, recall and f-measure;
· know how to use HTML5 for web page making;
· know how to describe link analysis techniques and the main link analysis algorithms for sorting search engine results;
· distinguish the characteristics of the main formats for the "data web", such as microdata, RDFa and JSON-LD;
· SEO techniques.
Knowledge: The student should possess knowledge relative to the retrieval of information on the internet with a particular emphasis on search engines and related techniques for word-processing, indexing and query processing. They will be able to describe the characteristics of the main models of repair (boolean vs. vector) and techniques to evaluate the effectiveness of recollection within the metrics of precision, recall and f-measurement. In addition, the student will need to have knowledge regarding the visibility of sites in terms of search engine availability (the so-called SEO - Search Engine Optimization). To do this, the student will need to know the main constructs of HTML5 language, link analysis techniques, as well as the definition of "data web", the various types of microdata and the impact that these ideas have on both on-site and off-site SEO techniques.
Skills: The student will acquire the following skills:
· distinguish the characteristics and application scopes of the Boolean recollection model from the vector model;
· know how to apply the techniques of text transformation, indexing and query processing of an information recollection system;
· know how to apply TF-IDF-based vector-based reperitable measurement techniques;
· know how to apply the evaluation techniques of an information recollection system based on precision, recall and f-measure;
· know how to use HTML5 for web page making;
· know how to describe link analysis techniques and the main link analysis algorithms for sorting search engine results;
· distinguish the characteristics of the main formats for the "data web", such as microdata, RDFa and JSON-LD;
· SEO techniques.
Lesson period: Second semester
Assessment methods: Esame
Assessment result: voto verbalizzato in trentesimi
Single course
This course cannot be attended as a single course. Please check our list of single courses to find the ones available for enrolment.
Course syllabus and organization
Single session
Responsible
Lesson period
Second semester
Course syllabus
The course is organized in two units.
The syllabus of unit A (20 hours - 3CFU) is about the following topics:
· Information retrieval and search engines
· Retrieval models (boolean model vs. vector space model)
· Text analysis techniques
· Web content indexing
· Query processing
· Evaluation of an information retrieval system
The syllabus of unit B (20 hours - 3CFU) is about the following topics:
· Link analysis techniques
· HTML5 notions
· Languages for the web of data
· SEO techniques (Search Engine Optimization)
· "on-site" SEO techniques
· "off-site" SEO techniques
The syllabus of unit A (20 hours - 3CFU) is about the following topics:
· Information retrieval and search engines
· Retrieval models (boolean model vs. vector space model)
· Text analysis techniques
· Web content indexing
· Query processing
· Evaluation of an information retrieval system
The syllabus of unit B (20 hours - 3CFU) is about the following topics:
· Link analysis techniques
· HTML5 notions
· Languages for the web of data
· SEO techniques (Search Engine Optimization)
· "on-site" SEO techniques
· "off-site" SEO techniques
Prerequisites for admission
No prerequisites are required.
Teaching methods
Lectures are based on frontal teaching with the support of slides and handouts that are progressively published on the reference course website (Arial platform). Throughout the lectures, the analysis of real case-studies is enforced with the aim at illustrating the application of theoretical course contents to concrete scenarios. Seminars are also planned with the participation of professional experts on web-communication topics.
Lecture attendance is not mandatory, but it is strongly recommended. Students have to attend at least two-thirds of the lectures for being considered as attending students.
Lecture attendance is not mandatory, but it is strongly recommended. Students have to attend at least two-thirds of the lectures for being considered as attending students.
Teaching Resources
The bibliography coincides for attending and non-attending students.
For the unit A, choose a book between:
· C.D. Manning, P. Raghavan, H. Schütze. Introduction to Information Retrieval. Cambridge University Press. 2008. Text in English, free download online.
Chapters: 1, 2, 3, 4, 6, 8, 19, 21.
· W.B. Croft, D. Metzler, T. Strohman. Search Engines, Information Retrieval in Practice. Pearson Education. 2015. Text in English, free download online.
Chapters: 1, 2, 3 (excluded 3.6 - 3.8), 4 (excluded 4.2.2, 4.6, 4.7), 5 (excluded 5.4 - 5.7), 6, 7.1, 8 (excluded 8.5 - 8.7).
For the unit B, choose a book between:
· M. Maltraversi. SEO e SEM. Guida avanzata al Web marketing (fourth edition). LSWR publishing. 2016. Text in Italian.
· E. Enge, S. Spencer, J.C. Stricchiola. The Art of SEO: Mastering Search Engine Optimization. O'Reilly publishing, third edition. 2015. Text in English. About this book, an Italian version from Flacowski publishing is also available with Jacopo Matteuzzi and Flavio Mazzanti (editors).
For the unit A, choose a book between:
· C.D. Manning, P. Raghavan, H. Schütze. Introduction to Information Retrieval. Cambridge University Press. 2008. Text in English, free download online.
Chapters: 1, 2, 3, 4, 6, 8, 19, 21.
· W.B. Croft, D. Metzler, T. Strohman. Search Engines, Information Retrieval in Practice. Pearson Education. 2015. Text in English, free download online.
Chapters: 1, 2, 3 (excluded 3.6 - 3.8), 4 (excluded 4.2.2, 4.6, 4.7), 5 (excluded 5.4 - 5.7), 6, 7.1, 8 (excluded 8.5 - 8.7).
For the unit B, choose a book between:
· M. Maltraversi. SEO e SEM. Guida avanzata al Web marketing (fourth edition). LSWR publishing. 2016. Text in Italian.
· E. Enge, S. Spencer, J.C. Stricchiola. The Art of SEO: Mastering Search Engine Optimization. O'Reilly publishing, third edition. 2015. Text in English. About this book, an Italian version from Flacowski publishing is also available with Jacopo Matteuzzi and Flavio Mazzanti (editors).
Assessment methods and Criteria
Attending students: the assessment method consists in a written exam and in a subsequent interview, both the assessments are mandatory. The written exam occurs around half the course lectures, it is about the syllabus of the unit A, it is composed of both open-ended and choice questions, and it is an hour long. The assessment criteria are the capability to clearly present knowledge, the completeness of answers, the correctness of reasoning in carrying out exercises. The result of the written exam is published on the reference course website (Arial platform). The interview occurs at the end of the course lectures, it is about the syllabus of the unit B, and it consists in the analysis of a case-study assigned by the teacher upon successful passing the written exam. The assessment criteria are the capability to fluidly arrange the knowledge presentation, the clear and effective presentation of critical positions/claims with respect to the considered case-study, the pertinence in using a specialized lexicon. The final result is expressed in thirtieths and it corresponds to the average evaluation calculated on the written exam and the interview.
Non-attending students: the assessment method consists in an interview on the syllabus of both unit A and B. The assessment criteria are the capability to fluidly arrange the knowledge presentation, the clear and effective presentation of critical positions/claims with respect to the teacher questions, the pertinence in using a specialized lexicon. The final result is expressed in thirtieths.
Incoming Erasmus students can take the exam in English according to a syllabus previously endorsed and confirmed by the teacher.
The assessment methods for students with handicap and/or learning disability is case-by-case defined by the teacher with the support of the competent authority.
Non-attending students: the assessment method consists in an interview on the syllabus of both unit A and B. The assessment criteria are the capability to fluidly arrange the knowledge presentation, the clear and effective presentation of critical positions/claims with respect to the teacher questions, the pertinence in using a specialized lexicon. The final result is expressed in thirtieths.
Incoming Erasmus students can take the exam in English according to a syllabus previously endorsed and confirmed by the teacher.
The assessment methods for students with handicap and/or learning disability is case-by-case defined by the teacher with the support of the competent authority.
Unita' didattica A
INF/01 - INFORMATICS - University credits: 3
Lessons: 20 hours
Professor:
Montanelli Stefano
Shifts:
-
Professor:
Montanelli Stefano
Unita' didattica B
INF/01 - INFORMATICS - University credits: 3
Lessons: 20 hours
Professor:
Montanelli Stefano
Shifts:
-
Professor:
Montanelli StefanoProfessor(s)
Reception:
By appointment to be arranged by email
Room 7015, Dipartimento di Informatica "Giovanni degli Antoni", Via Celoria 18 - 20133 Milano