Checking date: 20/05/2019


Course: 2019/2020

Advanced Techniques For Information Retrieval
(17303)
Study: Master in Libraries, Archives and Digital Continuity (335)
EPH


Coordinating teacher: MORATO LARA, JORGE LUIS

Department assigned to the subject: Department of Computer Science and Engineering

Type: Electives
ECTS Credits: 3.0 ECTS

Course:
Semester:




Competences and skills that will be acquired and learning results.
BASIC COMPETENCIES CB9 Students should know how to communicate their conclusions, knowledge and reasoning to specialized and non-specialized audiences, in a clear and unambiguous way GENERAL COMPETENCIES CG5 Acknowledge the growing importance of team-working in the labor market and show adaptability and integration capabilities in different work environments, keeping relationships and fluid communications. CG8 To value the quality of the work undertaken when planning, organizing and developing the activities related with the grade. The student should be able to show initiative, creativity and sense of the responsibility, keeping the interest during the process and showing commitment for results obtained. CG9 Integrate knowledge, report informed judgments and communicate conclusions, grounded in specialized knowledge and reasoning, to specialized and non-specialized audiences, in a clear and unambiguous way CG11 Ability to interpret, apply and innovate methodologies, technologies, policies, analysis, and information management and retrieval methods SPECIFIC COMPETENCIES CE1 Learn and analyze the current state and the future perspectives and application of these technologies in libraries and archives. CE6 Using metadata vocabularies and other semantic schema models for managing digital documents. CE7 Data visualization, using temporal techniques, geospatial, thematic and network analysis. LEARNING RESULTS In this course is specially important all the techniques that facilitates information exchange and publication of digital documents, specially in regard with Semantic Web technologies. After completing the course the student should know: 1. Evaluate the main Information Retrieval Systems, emphasizing retrieval on the Web and the Semantic Web. 2. Know how-to clean and augment data in BigData lyfecycle 3. Evaluate retrieval systems 4. Know how-to disseminate of documentation on the Web: search engine positioning and management 5. Learn formalisms and strategies to improve the interoperability and organization of documents 6. Know how to use the main retrieval languages in databases and the Semantic Web.
Description of contents: programme
Common contents in regard with the other subjects: - Using information retrieval systems and semantic schemas. Specific contents to the subject: - Search in different web types: Semantic web, social web, data web, question-answering web, deep web, dark web, commercial web. - Information retrieval systems for Big Data, documents (scrapers) and Linked Data - Evaluation metrics for information retrieval . - Knowledge management model of knowledge representation and organization of information and semantic Interoperability - Techniques of positioning and SEO tools that affect the indexing and retrieval - Fundamentals in information retrieval languages: SQL, SPARQL, Xpath, Regex Assigments: - Academic activities based on exercises and problems. - Seminar/Workshop based on use cases
Learning activities and methodology
LEARNING ACTIVITIES IN THE STUDY PLAN AF1 Individual work related with theoretical contents and practicalities delivered by the professor. AF2 Individual work for problem resolution and case study AF3 Theoretical and practical face-to-face classes AF4 Tutorial class AF5 Teamwork AF6 Active involvement in forums in the platform AF7 Self-assessment tests Activity cod Total hours Classroom classes % AF1 125 (32) 0 0 AF2 80 (30) 0 0 AF3 12 (3) 12 (3) 100 (100) AF4 10 (2) 0 0 AF5 124 (18) 0 0 AF6 5 (2) 0 0 AF7 4 (3) 0 0 TOTAL 360 (90) 12 (3) 3,3 (3,3) TEACHING METHODOLOGY MD1 Class presentations by the teacher, with computer and audiovisual resources, in these classes the basic concepts in the subject will be explained and a basic bibliography will be provided. MD2. Critical review of the text suggested by the teacher: articles, reports, manuals and research papers, to complement the teacher's material. MD3. Resolution of practical case studies and problems, to be solve in teams or individually. MD5. Report writing individually or in teams. MD6. Reading teaching theoretical and practical materials TUTORIAL CLASES Tutorial classes will be scheduled according the regulations provided by the University. They will be published in the e-leaning platform (Aula Global). There will be two types of tutorial classes, face-to-face and online. Students will ask for individual tutorial classes in different hours to those published.
Assessment System
  • % end-of-term-examination 20
  • % of continuous assessment (assigments, laboratory, practicals...) 80
Basic Bibliography
  • Baeza-Yates, Ricardo. Modern Information Retrieval. ACM Press. 2011
  • Dean Allemang, James Hendler. Semantic Web for the Working Ontologists: Effective Modelin in RDFS and OWL. Elservier. 2011
  • Verborgh, Ruben, De Wilde, Max. Using OpenRefine: the essential OpenRefine guide that takes you from data analysis and error fixing to linking your dataset to the Web. Packt Publishing. 2013
Recursos electrónicosElectronic Resources *
(*) Access to some electronic resources may be restricted to members of the university community and require validation through Campus Global. If you try to connect from outside of the University you will need to set up a VPN


The course syllabus and the academic weekly planning may change due academic events or other reasons.