INFORMATİON TECHNOLOGİES - Deneme Sınavı - 3

Discretization is the work of dividing the range of values of a continuous attribute into intervals. Data cleaning includes processes of filling missing values, correcting inconsistencies, identifying outliers and getting rid of them. Huge amount of data makes mining data in coherent time impossible. Thus data reduction techniques are utilized. Reducing number of tuples, dimensionality reduction and etc. are utilized techniques for data reduction. Data integration merges data from different sources such as database, data flats etc. into a compatible data store. Data transformation includes the technique of aggregation, generalization, normalization and attribute construction. Therefore, the correct option is D.

Data classification is a two-step process as training and prediction. In training step, a classifier model is created by analyzing data objects and their class labels. In a prediction step, unknown class labels of data objects are predicted using the generated classifier model. Decision tree induction is one of the mostly known classification techniques. Thus, it falls under the category of predictive data mining tasks. In training step, it generates a decision tree based on class labels of trained data objects. In a decision tree, each node represents a test on an attribute of data, each edge of that node represents a value for that attribute and each leaf represents a class label. Generating a decision tree is generally as a two-step process as tree construction and tree pruning. Therefore, the correct option is E.

If-Then rule, k-nearest neighbor, Bayesian classifiers and Naïve Bayesian classifiers are used for classification purposes. On the other hand, regression is one of the mostly known prediction algorithms. Therefore, the correct option is A.

Mining of Frequent Patterns is the process of mining patterns that frequently occurs in data. Data can be described with classes or concepts. These descriptions are inferred with data characterization and data discrimination. Data characterization is the process of summarizing the general properties of a class whereas data discrimination is the process of comparing class properties with features of other one or more classes. Association is referred as patterns frequently purchased together. Mining association is the process of discovering relations among data. Correlations represent relations between items or their attributes. Two items can be positively or negatively correlated. Moreover, there may be no correlation between two items as a result of mining correlation. Clustering brings together similar objects which do not have a class label. Therefore, the correct option is E.

Partitioning-based methods divide n objects into k partitions where k is smaller than or equal to n. In partitioning-based techniques, each partition contains at least one object and each object belongs to only one partition. Objects are divided hierarchically in hierarchical- based clustering. Hierarchical-based clustering methods can be classified as agglomerative and divisive approaches. Initially, each object represents a cluster in agglomerative approaches, then close clusters are merged consecutively until a termination condition holds or all objects or clusters are collected into one cluster. In divisive approaches, all objects are grouped into one cluster. Then, a cluster is divided into smaller clusters in each consecutive step until each object is assigned to one cluster or a termination condition holds. Density-based clustering methods group objects into clusters based on densities of clusters to represent clusters with arbitrary shape. An object in a cluster must have at least minimum number of neighbors in the neighborhood of a given radius. In model-based methods, objects are assigned to clusters based on defined models of clusters. Therefore, the correct option is C.

Metadata is generally referred as data about other data or catalog for a data. It describes, identifies, explains, manages, and uses a data resource. Metadata can be grouped as descriptive, structural and administrative metadata. Descriptive metadata identifies a data resource. Administrative metadata defines the ways of managing a data resource. Structural metadata describes relationships between parts of a composite object. Metadata can generally be stored in various storage structures such as a field of relational database’s table, XML files, RDF models. Therefore, the correct option is D.

Salient feature comparison of application software versus system software

System Software                       Application Software
Close to system                        Close to user
Fast in speed                            Slow in speed
Difficult to design                      Easy to design
Difficult to understand               Easy to understand
Less interactive                         More interactive
Smaller in size                          Bigger in size (requires large storage space)
Difficult to manipulate                         Easy to manipulate and use
Generally written in low-level language Generally written in high-level language

Salient feature comparison of application software versus system software

System Software                       Application Software
Close to system                        Close to user
Fast in speed                            Slow in speed
Difficult to design                      Easy to design
Difficult to understand               Easy to understand
Less interactive                         More interactive
Smaller in size                          Bigger in size (requires large storage space)
Difficult to manipulate                         Easy to manipulate and use
Generally written in low-level language Generally written in high-level language

A device driver is a system software that operates or controls a particular hardware device (e.g., graphic card, printer, scanner, etc.) that is connected to a computer. It allows a computer to communicate with these internal or external peripheral devices.

Applications software (also called end-user programs) include such things as database programs, word processors, Web browsers, spreadsheets, accounting applications, media players, photo editors and games.

Memory Management
OS keeps tracks of primary memory i.e. what part of it is in use by whom, what part is not in use etc. and allocates the memory when a process or program requests it. Programs to be executed by the computer systems first must be loaded into the main memory. A set of processes, together with the
data they access, reside in the memory.

A process must be in memory to be executed. OS manages memory in a way that many processes reside in memory simultaneously.

The main objectives of the operating system can be summarized as follows:
• Enables the users to use computer in a convenient and efficient manner
• Hides complexity of the hardware resources from the users
• Acts as an intermediary between the computer hardware and its users
• Manages the resources of a computer system
• To keep track of who is using which resource, granting resource requests,
according for resource using and mediating conflicting requests from different programs and users
• Provides efficient and fair sharing of resources among users and programs

States of a computer process
Description                                                                Processes State
The process is being created                                       New
Instructions are being executed                                   Running
The processes is waiting for certain event                     Waiting
The processes is ready to be assigned to a processor     Ready
The process has finished execution                               Terminated

In general, an office suite includes the following application software:
• A word processor
• A spreadsheet application
• A presentation software

Text related tasks such as composing, editing, formatting, and printing of text documents are carried out by word processor. Furthermore, word processing software allows users to
• change margins
• insert footnotes
• find and replace terms
• place a header and footer at the top and the bottom of a page
• use different fonts (character design), font size (character scale), and font style (character appearance such as bold, italic and underline).

A browser is a software to connect to the Internet (World Wide Web) and display Web pages.

Internet Relay Chat (IRC) is a protocol that facilitates synchronous communication in the form of text. It allows several users to chat each
other simultaneously.

Data can be referred as raw, unorganized facts and concepts which need to be processed. Information is organized, categorized, contextualized data. Data becomes meaningful with information. Information needs to be analyzed especially for making strategic decisions. Information does not need to be useful. Knowledge is simply defined as useful information. Wisdom is related with judging which knowledge is true and applying it to real life.
Data can be grouped as qualitative data and quantitative data. Quantitative data can be referred as data in numerical form whereas qualitative data can be referred as data different than numerical form. A quantitative or numeric data can be continuous or discrete. A continuous data can be any value from the specified range. A discrete data can be any one of the specified discrete numerical values. Qualitative data or categorical data can be grouped as nominal data and ordinal data. Unlike nominal data, categories are in certain orders in ordinal data.
Data can be collected explicitly or implicitly. Explicitly collecting data includes the ways which data is gained directly such as questionnaires, votes etc. Tracking user behaviors, keeping click through rate of a web site are some of the ways of implicitly collecting data.
Data is valuable when it is analyzed and used for gaining useful information. Thus, data needs to be managed in order to define, identify, describe, modify, destroy, mine, report data and so on. Data management includes topics such as data defining, data architecture management, data quality management, master data management, metadata management, database management, data warehousing, reporting and so on.
Extracting knowledge from data is extremely valuable since raw data is converted into useful, interesting form.

Qualitative data or categorical data can be grouped as nominal data and ordinal data. Unlike nominal data, categories are in certain orders in ordinal data.

Managing data is important and provides some advantages described as follows:
• It provides mechanisms to become data into accessible, reliable, authentic and complete form.
• Itprovides mechanisms to securely share data between information technology systems, applications, departments or employees for an enterprise.
• It helps decision makers to make strategic decisions by allowing mining and analyzing data.
• It allows organizing, tracking, deleting, creating, and reporting data.
• It disallows redundancy and loss in data.
• It minimizes damage caused by errors related with data.

Data warehousing keeps historical data for preprocessing, mining, analyzing, reporting data.