Information Systems Question Bank Lecture 7-10 PDF

Information Systems Module 24/25 Question bank lecture 7-10 # Lecture 7: OLAP tool that can involve simple summaries or complex groupings involving interrelated data. Roll up Involves analyzing complex relationships among thousands of data items stor...

Information Systems Module 24/25 Question bank lecture 7-10 # Lecture 7: OLAP tool that can involve simple summaries or complex groupings involving interrelated data. Roll up Involves analyzing complex relationships among thousands of data items stored in data warehouses and other multidimensional databases to discover patterns, trends, and exception conditions. Online Analytical Processing (OLAP) OLAP that can display detailed data that comprise aggregate data. Drill down Information system that applies analytical models on information from TPS and MIS. Decision Support System (DDS) Information system used by senior management which uses summarized information from internal MIS and DSS to address non-routine decisions requiring judgment and evaluation. Executive Support System (ESS) A computerized system that serves operational level to perform and record daily routine transactions. Transaction Processing System (TPS) Operation performed along a time axis to find time-based patterns in the data warehouse. Slicing and Dicing Transaction is business-related exchange such as payments to employees/suppliers and sales to customers. OLAP operations include Roll-Up, Drill-Down, and Slicing and dicing. OLAP is considered a Business Intelligence (BI) tool. ______________________________________________________________________________ ______ #Lecture 8: The study, planning, and design of how people and computers work together. Human-Computer interaction A specialist whose responsibility is to determine user personas. UX designer The area of tech that involves how users interact with websites and applications and aims to improve the experience a user has when they visit a website or use an app. UX A user interface guideline that recommends displaying messages at a logical place on the screen and allowing messages to remain on the screen long enough for users to read them. Providing Feedback to users A specialist whose responsibility is designing interface elements such as buttons, icons, sliders, and animations. UI designer #Lecture 9: Process of affecting visibility of a website in SE unpaid results, called natural/organic results. Search Engine Optimization (SEO) A fundamental and simple technique used in Natural Language Processing (NLP) and Text Mining to convert text into numerical features. Bag of Words (BoW) Reducing words to their root form. Stemming A process that involves a series of steps to clean and transform raw text into a format that is suitable for analysis, indexing, and retrieval. Text preprocessing Splitting text into individual words or terms. Tokenization Removing common words like "the", "and “, “I”, and “is”. Text preprocessing (Removing stop words) The automation of activities that we associate with human thinking, activities such as decision making, problem solving, and learning. Artificial intelligence  A natural language text that requests the GEN AI to perform a specific task. Prompt A subset of AI algorithms that have the ability to learn from data without being explicitly programmed. Machine Learning The process of tailoring the foundation model to a specific gen AI application. Tuning It refers to a set of algorithms that tries to mimic human neural systems, also known as neural networks. Deep Learning #Lecture 10: Match people with similar interests as a basis for recommendation. Collaborative Filtering Many empty cells in the user/item rating matrix. Unrated item Recommend items by predicting the utility of items for a particular user based on how ‘similar’ the items are to those that he/she has liked in the past. Content-based recommenders Obtaining data from users independently. Stalking Creating user profiles through observing and recording user behavior. Implicit User profile Systems that help businesses make more profits by selling more products. Recommender Systems