- Files and Data bases (Bachelor in Informatics Engineering, 2nd Course, Semester 2nd, Compulsory) - Object oriented programming (Bachelor in Informatics Engineering, 1st Course, 2nd Semester, Compulsory)

(Competences related with the ABET program are displayed in parentheses) General Competences: - Systematic acquisition of theoretical concepts (PO: i) - Ability to organize and communicate results (PO:g) - Ability to apply theoretical concepts in real-world scenarios (PO:a, b, c, e, k) - Teamwork (PO:d) - Problem solving in multidisciplinary contexts (PO:c) Specific Competences: - Cognitive (PO:a, c, j, k) 1. Retrieval models 2. Natural Language Processing Techniques 3. Systems to formalize, synthesize, and structure information 4. Traceability systems 5. Ability to show results in an appropriate way 6. Improve retrieval and knowledge reuse systems in the Web and in Software Engineering - Procedimental/Instrumental Competences (PO:a, b, c, e, j) 1. Design of Retrieval Systems 2. Design of natural language analyzers 3. Application of text mining techniques to improve the representation and sorting of results - Attitudinal Competences (PO: c, e, i) 1. Concern for quality results 2. Capability to solve problems in an autonomous manner 3. Encouragement to independent research and acquisition of knowledge necessary to solve problems

Description: Retrieval Models, Natural Language Processing, semantic analysis, metadata, linked data, information retrieval, positioning techniques, knowledge reuse, data mining The course examines fundamental concepts about retrieval systems, introducing a variete of basic techniques. This includes the use of knowledge organization systems, positioning techniques, natural language processing techniques and resources, and evaluation by retrieval metrics. Course content, 3 units: Unit 1. Information retrival - Lesson 1: Search basics in different web types: classic web, Semantic Web, Social Web, Data Web, Dark Web, Deep Web, question-answering web, and commercial web. - Lesson 2: Search Engine Optimization (SEO/SEM) - Lesson 3. Basic information retrieval models - Lesson 4: Access, acquisition and cleansing of semantic web data and bigdata - Lesson 5. Crawlers, scrapers and search engine arquitecture Unit 2. Retrieval evaluation - Lesson 6. Evaluation metrics for information retrieval systems Unit 3. Advanced techniques for information retrieval systems - Lesson 7. Natural Language Processing (NLP) - Lesson 8. Information extraction techniques (IE) - Lesson 9. Relevance feedback and query expansion

Theoretical lectures: 1.5 ECTS. To achieve the specific cognitive competences of the course (PO: a, c, j, k) Practical lectures: 1.5 ECTS. To develop the attitudinal and specific competences as well as most of the general ones, such as collaborative teamwork, skills to apply theoretical concepts, design planning, information organization, analysis, and abstraction. Students must design and develop an information retrieval system. Practical exercises deal with web positioning algorithms and retrieval metrics and technologies (PO: a, b, c, d, e, i, j) - Academic activities with the professor: 1 ECTS. Students must carry on collaborative work to evaluate their ability to apply theoretical concepts and meet the desired needs. (PO: a, b, c, d, e, g, k) - Guided academic activities (absent teacher): 0.5 ECTS. Complementary homework and technical readings suggested by the professor (PO: j) Exercises and examination: 1.5 ECTS. The goal is to complete the development of specific cognitive and procedural capacities. Exercises and results of the practices will be discussed in class. (PO: a, c, g) The course includes two hours per week of one-on-one tutorial