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10. Describe the k-nearest neighbor (kNN) data mining algorithm. (CH5: Diff: 2 Page Ref: 274) Answer: k-NN is a prediction method for ________ as well as regression-type ________problems. k-NN is a type of ________-based learning (or lazy learning) where the _________ is only approximated locally and all computations are deferred until the actual prediction. For instance, in the classification-type prediction, a case is classified by a majority vote of its neighbors with the object being assigned to the class most common among its k nearest neighbors. classification; prediction; instance; function prediction; classification; instance; function instance; function; classification; prediction instance; classification; prediction; function

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13. What is search engine optimization (SEO) and why is it important for organizations that own Web sites? (CH7: Diff: 3 Page Ref: 436-7) Answer: Search engine optimization (SEO) is the intentional activity of affecting the ________ of an e-commerce site or a Web site in a search engine's natural (unpaid or organic) ________ results. In general, the higher ranked on the search results page, and the more ________ a site appears in the search results list, the more visitors it will ________ from the search engine's users. Being indexed by search engines like Google, Bing, and Yahoo! is not good enough for businesses. Getting ranked on the most widely used search engines and getting ranked higher than your competitors are what make the difference. visibility; search; frequently; receive frequently; visibility; search; receive search; frequently; visibility; receive visibility; frequently; receive; search

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15. Can customer relationship management (CRM) systems and revenue management systems (RMS) recommend not selling a particular product to certain customers? If so, why; if not, why not? (CH8: Diff: 3 Page Ref: 468) Answer: Yes, CRM and RMS can ________ ignoring certain customers or not selling a bundle of products to a particular set of customers. Part of this effort involves identifying lifelong customer profitability. These approaches rely heavily on ________ techniques, which are typically described as ________ analytics. These systems attempt to predict who their best (i.e., most profitable) customers (and worst ones as well) are and focus on ________ products and services—or none at all—at appropriate prices to appeal to them. recommend; forecasting; predictive; identifying predictive; identifying; recommend; forecasting predictive; recommend; forecasting; identifying recommend; predictive; identifying; forecasting

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19. Describe why autonomous trucks would have a massively disruptive effect on jobs in the transportation industry. (CH10:Diff: 2 Page Ref: 600) Answer: Truck-based transportation in the US ________ a significant number of jobs throughout the country. If autonomous trucks were ________ and deployed this would have a massively disruptive effect on the industry. Many would argue that autonomous trucking would be less expensive and safer than trucks ________ by humans, and thus would be adopted significantly by corporations. This would _________a large portion of the workforce, and that would have negative economic effects. provides; approved; driven; displace approved; provides; driven; displace driven; displace; provides; approved displace; provides; approved; driven

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20. Discuss some of the security concerns surrounding the Pepper robot. (CH10: Diff: 2 Page Ref: 592) Answer: Pepper has several ________concerns that were pointed out by Scandinavian researchers. According to them, it is easy to have ________ root-level access to the bot. They also found the robot to be prone to brute force attacks. Pepper's functions can be ________ using various application programming interfaces (APIs) through languages such as Python, Java, and C + +. This feature can cause it to provide access to all its sensors, making it not secure. An attacker can establish a connection and then use Pepper's mic, camera, and other features to spy on people and their conversations. This is an ________ issue for many robots and smart speakers. security; unauthenticated; programmed; ongoing programmed; security; unauthenticated; ongoing unauthenticated; programmed; ongoing; security unauthenticated; programmed; security; ongoing

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22. Briefly describe benefits (process gains) derived from working in groups. (CH 11: Diff: 2 Page Ref: 615-16) Answer: It provides ________. Groups are better than individuals at understanding problems. People readily take _________ of problems and their solutions. They take responsibility. Group members have their egos embedded in the decision, so they are committed to the solution. Groups are better than individuals at catching errors. A group has more ________ (i.e., knowledge) than any one member. Group members can combine their knowledge to create new knowledge. More and more creative alternatives for problem-solving can be generated, and better solutions can be derived (e.g., through stimulation). A group may produce ________ during problem-solving. The effectiveness and/or quality of group work can be greater than the sum of what is produced by independent individuals. Working in a group may stimulate the creativity of the participants and the process. A group may have better and more precise communication working together. Risk propensity is balanced. Groups moderate high-risk takers and encourage conservatives. learning; ownership; information; synergy synergy; learning; ownership; information information; synergy; learning; ownership ownership; information; learning; synergy

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27. Discuss the major steps in the implementation of intelligent systems. (CH 14: Diff: 2 Page Ref: 729-30) Answer: Step 1 ________. Need assessment needs to provide the business case for the intelligent systems, including their major parts. Step 2 _________. In this step, it is necessary to examine the organization readiness for analytics and AI. It is necessary to check available resources, employees' attitudes for the change, projects' priorities, and so on. Step 3 ________. Organizations need to decide on in-house or outsourcing approach (make or buy) or on a combination of the two and possibly with partnership with a vendor or another company. A consultant may help at this step. Step 4 ________. Regardless of who will develop the system, certain activities need to be done. These include security, integration with other systems, project management preparation, and other activities. Step 5 Impact assessment. It is necessary to check the performance of the systems against plans. Need assessment; Preparations; System acquisition; System development Preparations; Need assessment; System acquisition; System development Need assessment; System acquisition; Preparations; System development Preparations; Need assessment; System acquisition; System development

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4. Describe the Turing test. (CH2: Diff: 3 Page Ref: 85) Answer: According to this test, a computer can be considered ________ only when a human interviewer asking the same questions to both an unseen ________ and an unseen computer cannot determine which is which. This test is limited to a question-and-answer (Q&A) mode. To pass the Turing Test, a ________ needs to be able to understand a human language (NLP), to possess human ________ (e.g., have a knowledge base), to reason using its stored knowledge, and to be able to learn from its experiences (machine learning). smart; human; computer; intelligence computer; smart; human; intelligence intelligence; smart; human; computer human; intelligence; computer; smart

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7. Describe the difference between quantitative and qualitative data. Include definitions for nominal and ordinal data. (CH4: Diff: 2 Page Ref: 213) Answer: Quantitative data are measured using _______ values, or numeric data. Qualitative data, also known as categorical data, contain both ________ and ordinal data. Nominal data have finite ________ values. Ordinal data have finite ________ values. Quantitative data can be readily represented by some sort of probability distribution. Qualitative data can be coded to numbers and then described by frequency distributions. numeric; nominal; nonordered; ordered ordered; numeric; nominal; nonordered nonordered; numeric; nominal; ordered nonordered; ordered; numeric; nominal

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1. Describe the types of computer support that can be used for structured, semistructured, and unstructured decisions. (CH1: Diff: 2 Page Ref: 15-16) Answer: Structured Decisions: Structured problems, which are encountered repeatedly, have a high level of __________. It is therefore possible to abstract, analyze, and classify them into specific categories and use a scientific approach for automating portions of this type of managerial decision making. Semistructured Decisions: Semistructured problems may involve a combination of standard solution procedures and human __________. Management science can provide models for the portion of a decision-making problem that is structured. For the unstructured portion, a DSS can improve the quality of the information on which the decision is based by providing, for example, not only a single solution but also a range of alternative __________, along with their potential impacts. Unstructured Decisions: These can be only partially supported by standard computerized __________ methods. It is usually necessary to develop customized solutions. However, such solutions may benefit from data and information generated from corporate or external data sources. solutions; quantitative; structure; judgment structure; judgment; solutions; quantitative judgment; solutions; structure; quantitative quantitative; structure; judgment; solutions

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14. What is the difference between white hat and black hat SEO activities? (CH7: Diff: 3 Page Ref: 437-8) Answer: An SEO technique is considered a white hat if it conforms to the search engines' ________ and involves no deception. Because search engine guidelines are not written as a series of rules or commandments, this is an important ________ to note. White-hat SEO is not just about following guidelines, but about ensuring that the ________a search engine indexes and subsequently ranks is the same content a user will see. Black-hat SEO attempts to improve rankings in ways that are disapproved by the search engines, or involve deception or trying to trick search engine ________from their intended purpose. content; guidelines; distinction; algorithms guidelines; distinction; content; algorithms distinction; content; guidelines; algorithms algorithms; guidelines; distinction; content

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21. List and briefly describe the major types of crowdsourcing. (CH 11: Diff: 3 Page Ref: 633-34) Answer: Collective intelligence (or wisdom). People in crowds are ________ problems and providing new insights and ideas leading to product, process, or service innovations. Crowd creation. People are ________ various types of content and sharing it with others (for pay or free). The created content may be used for problem-solving, advertising, or knowledge accumulation. Content creation can also be done by splitting large tasks into small segments (e.g., contributing content to create Wikipedia). Crowd voting. People are giving their opinions and ratings on ideas, products, or services, as well as ________ and filtering information presented to them. An example is voting in American Idol competitions. Crowd support and funding. People are ________ and supporting endeavors for social or business causes, such as offering donations, and micro-financing new ventures. evaluating; solving; creating; contributing solving; creating; evaluating; contributing creating; evaluating; solving; contributing contributing; solving; creating; evaluating

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25. Describe what the IoT is. (CH 13: Diff: 2 Page Ref: 690) Answer: The IoT is a connected network in which: Large numbers of _______ (things) can be connected. Each thing has a unique definition (IP address). Each thing has the ability to receive, send, and store ________automatically. Each thing is delivered mostly over the wireless ________. Each thing is built upon machine-to-machine (M2M) ________. Internet; communication; objects; data objects; data; Internet; communication data; Internet; objects; communication communication; objects; data; Internet

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3. Discuss the drivers of AI. (CH2: Diff: 2 Page Ref: 79) Answer: The use of AI has been driven by the following forces: People's interest in ________ machines and artificial brains The low cost of AI applications versus the high cost of manual labor (doing the same work) The desire of large tech companies to capture ________ advantage and market share of the AI market and their willingness to invest billions of dollars in AI The pressure on management to increase ________ and speed The availability of quality data contributing to the progress of AI The increasing ________ and reduced cost of computers in general The development of new technologies, particularly cloud computing productivity; smart; competitive; functionalities smart; competitive; productivity; functionalities functionalities; smart; competitive; productivity competitive; smart; productivity; functionalities

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8. Briefly describe seven techniques (or algorithms) that are used for classification modeling. (CH4: Diff: 2 Page Ref: 226) Answer: Decision tree analysis. Decision tree analysis (a machine-learning technique) is arguably the most popular ________ technique in the data mining arena. Statistical analysis. Statistical techniques were the primary classification algorithm for many years until the emergence of machine-learning techniques. Statistical classification techniques include ________regression and discriminant analysis. Neural networks. These are among the most popular machine-learning techniques that can be used for classification-type problems. Case-based reasoning. This approach uses ________cases to recognize commonalities in order to assign a new case into the most probable category. Bayesian classifiers. This approach uses ________ theory to build classification models based on past occurrences that are capable of placing a new instance into a most probable class (or category). Genetic algorithms. This approach uses the analogy of natural evolution to build directed-search-based mechanisms to classify data samples. Rough sets. This method takes into account the partial membership of class labels to predefined categories in building models (collection of rules) for classification problems. probability; classification; logistic; historical classification; logistic; historical; probability historical; classification; logistic; probability logistic; historical; classification; probability

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17. List and describe the three main "V"s that characterize Big Data. (CH9: Diff: 2 Page Ref: 514-15) Answer: Volume: This is obviously the most common trait of Big Data. Many factors contributed to the ________ increase in data volume, such as transaction-based data stored through the years, text data constantly streaming in from social media, increasing amounts of sensor data being collected, automatically generated RFID and GPS data, and so forth. Variety: Data today comes in all types of formats—ranging from ________ databases to hierarchical data stores created by the end-users and OLAP systems, to text documents, e-mail, XML, meter-collected, sensor-captured data, to video, audio, and stock ticker data. By some estimates, 80 to 85 percent of all organizations' data is in some sort of ________ or semistructured format Velocity: This refers to both how ________ data is being produced and how fast the data must be processed (i.e., captured, stored, and analyzed) to meet the need or demand. RFID tags, automated sensors, GPS devices, and smart meters are driving an increasing need to deal with torrents of data in near-real time. traditional; unstructured; fast; exponential unstructured; fast; exponential; traditional exponential; traditional; unstructured; fast traditional; unstructured; exponential; fast

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23. List and briefly describe the major components of expert systems. (CH 12: Diff: 3 Page Ref: 653-4) Answer: The major components in typical expert systems include: Knowledge ________. Mostly from human experts, is usually obtained by knowledge engineers. This knowledge, which may derive from several sources, is integrated, validated, and verified. Knowledge ________. This is a knowledge repository. The knowledge is divided into knowledge about the domain and knowledge about problem-solving and solution procedures. Also, the input data provided by the users may be stored in the knowledge base. Knowledge ________. This is frequently organized as business rules (also known as production rules). Inference ________. Also known as the control structure or the rule interpreter, this is the "brain" of ES. It provides the reasoning capability, namely the ability to answer users' questions, provide recommendations for solutions, generate predictions, and conduct other relevant tasks. The engine manipulates the rules by either forward chaining or backward chaining. In 1990s ES started to use other inference methods. User interface. This component allows user inference engine interactions. In classical ES, this was done in writing or by using menus. In today's knowledge systems, it is done by natural languages and voice. engine; acquisition; base; representation representation; acquisition; base; engine acquisition; base; representation; engine acquisition; representation; engine; base

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6. What is the difference between correlation and regression? (CH3: Diff: 3 Page Ref: 151) Answer: Correlation makes no a ________assumption of whether one variable is ________on the other(s) and is not concerned with the relationship between variables; instead it gives an estimate on the degree of association between the variables. On the other hand, regression attempts to describe the dependence of a ________variable on one (or more) ________variables where it implicitly assumes that there is a one-way causal effect from the explanatory variable(s) to the response variable, regardless of whether the path of effect is direct or indirect. Also, although the correlation is interested in the low-level relationships between two variables, regression is concerned with the relationships between all explanatory variables and the response variable. dependent; priori; response; explanatory dependent; response; priori; explanatory priori; dependent; response; explanatory explanatory; priori; dependent; response

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11. What are the key attributes of cognitive computing systems? (CH6: Diff: 3 Page Ref: 372) Answer: Cognitive computing systems must have the following key attributes as defined by the Cognitive Computing Consortium (2018): Adaptive: Cognitive systems must be flexible enough to _______as information changes and goals evolve. The systems must be able to digest dynamic data in real-time and make adjustments as the data and environment change. Interactive: Human-computer interaction (HCI) is a critical component in cognitive systems. Users must be able to ________ with cognitive machines and define their needs as those needs change. The technologies must also be able to interact with other processors, devices, and cloud platforms. Iterative and stateful: Cognitive computing technologies can also ________ problems by asking questions or pulling in additional data if a stated problem is vague or incomplete. The systems do this by maintaining information about similar situations that have previously occurred. Contextual: Understanding context is critical in thought processes, so cognitive systems must understand, identify, and mine contextual data, such as syntax, time, location, domain, requirements, and a specific user's profile, tasks, or goals. Cognitive systems may ________on multiple sources of information, including structured and unstructured data and visual, auditory, or sensor data. identify; draw; learn; interact interact; learn; identify; draw draw; learn; interact; identify learn; interact; identity; draw

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12. How does cognitive computing differ from artificial intelligence? (CH6: Diff: 2 Page Ref: 373) Answer: Technologies - both technologies utilize machine learning, and LP, neural networks, and deep learning: but cognitive computing adds _____ mining and sentiment analysis Capabilities offered - while AI seeks to find _____patterns in data sources, cognitive computing attempts to simulate the human thought process to find solutions Purpose - AI seeks to automate _____ processes whereas cognitive computing seeks to augment human capability Industries - both have applications in most industries, but the focus of cognitive computing is currently in _____ service, marketing, healthcare, entertainment, and services customer; text; hidden; complex complex; text; hidden; customer customer; text; hidden; complex text; hidden; complex; customer

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16. Compare and contrast decision-making under uncertainty, risk, and certainty. (CH8: Diff: 2 Page Ref: 471-2 Answer: In decision-making under certainty, it is assumed that ________ knowledge is available so that the decision-maker knows exactly what the outcome of each course of action will be (as in a deterministic environment). In decision-making under uncertainty, the decision-maker considers situations in which several outcomes are ________ for each course of action. In contrast to the risk situation, in this case, the decision-maker does not know, or cannot estimate, the probability of occurrence of the possible outcomes. Decision-making under uncertainty is more difficult than decision-making under certainty because there is ________ information. In decision making under risk (also known as a probabilistic or stochastic decision-making situation), the decision-maker must consider several possible outcomes for each alternative, each with a given ________ of occurrence. possible; insufficient; complete; probability insufficient; complete; possible; probability probability; complete; possible; insufficient complete; possible; insufficient; probability

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18. What is NoSQL as used for Big Data? Describe its major downsides. (CH9: Diff: 2 Page Ref: 528-29) Answer: NoSQL is a new style of database that has emerged to, like Hadoop, process large ________ of multi-structured data. However, whereas Hadoop is adept at supporting large-scale, batch-style historical analysis, NoSQL databases are aimed, for the most part (though there are some important exceptions), at serving up discrete data stored among large volumes of multi-structured data to end-user and automated Big Data applications. This capability is sorely lacking from ________ database technology, which simply can't maintain needed application performance levels at Big Data scale. The downside of most NoSQL databases today is that they trade ACID (atomicity, consistency, isolation, durability) ________ for performance and _________. Many also lack mature management and monitoring tools. scalability; volumes; relational; compliance compliance; volumes; relational; scalability scalability; volumes; relational; compliance volumes; relational; compliance; scalability

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2. List and describe three levels or categories of analytics that are most often viewed as sequential and independent, but also occasionally seen as overlapping. (CH1: Diff: 3 Page Ref: 31-35) Answer: Descriptive or reporting analytics refers to knowing what is happening in the organization and understanding some underlying _________ and causes of such occurrences. Predictive analytics aims to determine what is likely to happen in the future. This analysis is based on statistical _________ as well as other more recently developed techniques that fall under the general category of data ________. Prescriptive analytics recognizes what is going on as well as the likely forecast and make ________ to achieve the best performance possible. decisions; trends; techniques; mining mining; decisions; trends; techniques mining; trends; techniques; decisions trends; techniques; mining; decisions

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24. List and briefly describe the three classes of bots. (CH 12: Diff: 3 Page Ref: 661) Answer: Bots can be classified by their capabilities; three classes follow: ________. These are essentially conversational intelligent ________. They can do simple, usually repetitive, tasks for their owners, such as showing their bank's debits, helping them to purchase goods online, and to sell or buy stocks online. ________. In this category, we include more capable bots, for example, those that can stimulate conversations with people. This chapter deals mainly with chatbots. ________. These have a knowledge base that is improving with experience. That is, these bots can learn, for example, a customer's preferences. Chatbots; Intelligent bots; Regular bots; agents agents; Chatbots; Intelligent bots; Regular bots agents; Chatbots; Regular bots; Intelligent bots Regular bots; agents; Chatbots; Intelligent bots

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26. Discuss the four ways that IoT can drive marketing. (CH 13: Diff: 2 Page Ref: 702) Answer: ________. IoT collects more data about customers from more data sources than other technologies do. This includes data from wearables, smart homes, and everything consumers do. In addition, IoT provides data about changes in consumer preferences and behavior. ________. IoT can provide more accurate information about specific customers buying decisions, for example. IoT can identify customer expectations and direct customers to specific brands. _________. IoT can monitor environments regarding ad delivery for specific places, customers, methods, and campaigns. IoT can facilitate research of the business environment; factors such as competition, pricing, weather conditions, and new government regulations are observed. _________. IoT initiatives expand and enrich the digital channel of conversations between customers and vendors, especially those using wireless digital engagement. IoT also provides insight into consumer purchasing paths. In addition, marketers will receive improved customized market research data (e.g., by following the manner of customers' engagement and how customers react to promotions). Real-time personalization; Disruptive data collection; Environmental attribution; Complete conversation path Environmental attribution; Disruptive data collection; Real-time personalization; Complete conversation path Disruptive data collection; Environmental attribution; Complete conversation path; Real-time personalization Disruptive data collection; Real-time personalization; Environmental attribution; Complete conversation path

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28. Discuss how the growth in analytics can affect organizational structure. (CH 14: Diff: 3 Page Ref: 741 Answer: An often-cited change in organizational _______ as additional _______and DI projects are undertaken is the growth or creation of a separate analytics, DI or data science department. This may be a holy new department or be created from or into existing MIS departments. With this growth comes the creation of new positions related to these specialties and possibly the elimination of old ________that have become less relevant to overall company ________. Conversely, in other organizations, this results in embedding analytics specialties within each functional area (such as marketing, operations, or finance). analytics; structure; positions; strategy positions; structure; analytics; strategy strategy; structure; analytics; positions structure; analytics; positions; strategy

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5. Describe the use of both Gantt and Pert charts. (CH3: Diff: 2 Page Ref: 173) Answer: A Gantt chart is a special case of ________bar charts used to portray project ________, project tasks/activity durations, and overlap among the tasks/activities. By showing start and end dates/times of tasks/activities and the overlapping relationships, Gantt charts provide invaluable aid for management and control of projects. For instance, Gantt charts are often used to show project timelines, task overlaps, relative task completions (a partial bar illustrating the completion percentage inside a bar that shows the actual task duration), resources assigned to each task, milestones, and deliverables. The PERT chart (also called a network diagram) is developed primarily to simplify the ________ and scheduling of large and complex projects. A PERT chart shows ________ relationships among project activities/tasks. It is composed of nodes (represented as circles or rectangles) and edges (represented with directed arrows). Based on the selected PERT chart convention, either nodes or the edges can be used to represent the project activities/tasks (activity-on-node versus activity-on-arrow representation schema). planning; horizontal; timelines; precedence precedence; horizontal; timelines; planning timelines; planning; horizontal; precedence horizontal; timelines; planning; precedence

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9. Why have neural networks shown much promise in many forecasting and business classification applications? (CH5: Diff: 2 Page Ref: 255) Answer: Neural networks ________a brain metaphor for information processing. Neural networks have shown much promise in many ________ and business classification applications because of their ability to "_______" from the data, their nonparametric nature (i.e., no rigid assumptions), and their ability to ________. Neural computing refers to a pattern-recognition methodology for machine learning. The resulting model from neural computing is often called an artificial neural network (ANN) or a neural network. generalize; represent; forecasting; learn learn; represent; forecasting; generalize forecasting; learn; generalize; represent represent; forecasting; learn; generalize

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