Behavioral Targeting Online Advertising

With the rapid growth of the online advertising market, Behavioral Targeting (BT), which delivers advertisements to users based on understanding of their needs through their behaviors, is attracting more attention. The amount of spend on behaviorally targeted ad spending in the US is projected to reach $4.4 billion in 2012 (Hallerman, 2008). BT is a complex technology, which involves data collection, data mining, audience segmentation, contextual page analysis, predictive modeling and so on. This chapter gives an overview of Behavioral Targeting by introducing the Behavioral Targeting business, followed by classic BT research challenges and solution proposals. We will also point out BT research challenges which are currently under-explored in both industry and academia.

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Privacy and Confidentiality Issues in Data Mining

Data Warehousing and Mining ◽

10.4018/978-1-59904-951-9.ch180 ◽

2008 ◽

pp. 2850-2855

Author(s):

Yücel Saygin

Keyword(s):

Data Mining ◽

New York ◽

Data Collection ◽

New York Times ◽

Computer Assisted ◽

Terrorist Organizations ◽

Confidential Data ◽

The Us ◽

Privacy And Confidentiality ◽

Mining Tools

Data regarding people and their activities have been collected over the years, which has become more pervasive with widespread usage of the Internet. Collected data usually are stored in data warehouses, and powerful data mining tools are used to turn it into competitive advantage. Besides businesses, government agencies are among the most ambitious data collectors, especially in regard to the increase of safety threats coming from global terrorist organizations. For example, CAPPS (Computer Assisted Passenger Prescreening System) collects flight reservation information as well as commercial information about passengers. This data, in turn, can be utilized by government security agencies. Although CAPPS represents US national data collection efforts, it also has an effect on other countries. The following sign at the KLM ticket desk in Amsterdam International Airport illustrates the international level of data collection efforts: “Please note that KLM Royal Dutch Airlines and other airlines are required by new security laws in the US and several other countries to give security customs and immigration authorities access to passenger data. Accordingly, any information we hold about you and your travel arrangements may be disclosed to the concerning authorities of these countries in your itinerary.” This is a very striking example of how the confidential data belonging to citizens of one country could be handed over to authorities of some other country via newly enforced security laws. In fact, some of the largest airline companies in the US, including American, United, and Northwest, turned over millions of passenger records to the FBI, according to the New York Times (Schwartz & Maynard, 2004).

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The Importance of Data Within Contemporary CRM

Data Mining Applications for Empowering Knowledge Societies ◽

10.4018/978-1-59904-657-0.ch006 ◽

2009 ◽

pp. 96-109 ◽

Cited By ~ 4

Author(s):

Diana Luck

Keyword(s):

Data Mining ◽

Data Collection ◽

Data Storage ◽

Relationship Management ◽

Cost Savings ◽

Customer Relationship ◽

Evidence Based ◽

Essential Components ◽

Collection Data ◽

Data Collation

In recent times, customer relationship management (CRM) has been defined as relating to sales, marketing, and even services automation. Additionally, the concept is increasingly associated with cost savings and streamline processes as well as with the engendering, nurturing and tracking of relationships with customers. Much less associations appear to be attributed to the creation, storage and mining of data. Although successful CRM is in evidence based on a triad combination of technology, people and processes, the importance of data is unquestionable. Accordingly, this chapter seeks to illustrate how, although the product and service elements as well as organizational structure and strategies are central to CRM, data is the pivotal dimension around which the concept revolves in contemporary terms. Consequently, this chapter seeks to illustrate how the processes associated with data management, namely: data collection, data collation, data storage and data mining, are essential components of CRM in both theoretical and practical terms.

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Privacy and Confidentiality Issues in Data Mining

Encyclopedia of Data Warehousing and Mining ◽

10.4018/978-1-59140-557-3.ch173 ◽

2011 ◽

pp. 921-924

Author(s):

Yücel Saygin

Keyword(s):

Data Mining ◽

New York ◽

Data Collection ◽

New York Times ◽

Computer Assisted ◽

Terrorist Organizations ◽

Confidential Data ◽

The Us ◽

Privacy And Confidentiality ◽

Mining Tools

Data regarding people and their activities have been collected over the years, which has become more pervasive with widespread usage of the Internet. Collected data usually are stored in data warehouses, and powerful data mining tools are used to turn it into competitive advantage. Besides businesses, government agencies are among the most ambitious data collectors, especially in regard to the increase of safety threats coming from global terrorist organizations. For example, CAPPS (Computer Assisted Passenger Prescreening System) collects flight reservation information as well as commercial information about passengers. This data, in turn, can be utilized by government security agencies. Although CAPPS represents US national data collection efforts, it also has an effect on other countries. The following sign at the KLM ticket desk in Amsterdam International Airport illustrates the international level of data collection efforts: “Please note that KLM Royal Dutch Airlines and other airlines are required by new security laws in the US and several other countries to give security customs and immigration authorities access to passenger data. Accordingly, any information we hold about you and your travel arrangements may be disclosed to the concerning authorities of these countries in your itinerary.” This is a very striking example of how the confidential data belonging to citizens of one country could be handed over to authorities of some other country via newly enforced security laws. In fact, some of the largest airline companies in the US, including American, United, and Northwest, turned over millions of passenger records to the FBI, according to the New York Times (Schwartz & Maynard, 2004).

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The Importance of Data Within Contemporary CRM

Business Information Systems ◽

10.4018/978-1-61520-969-9.ch124 ◽

2010 ◽

pp. 2041-2054

Author(s):

Diana Luck

Keyword(s):

Data Mining ◽

Data Collection ◽

Data Storage ◽

Relationship Management ◽

Cost Savings ◽

Customer Relationship ◽

Evidence Based ◽

Essential Components ◽

Collection Data ◽

Data Collation

In recent times, customer relationship management (CRM) has been defined as relating to sales, marketing, and even services automation. Additionally, the concept is increasingly associated with cost savings and streamline processes as well as with the engendering, nurturing and tracking of relationships with customers. Much less associations appear to be attributed to the creation, storage and mining of data. Although successful CRM is in evidence based on a triad combination of technology, people and processes, the importance of data is unquestionable. Accordingly, this chapter seeks to illustrate how, although the product and service elements as well as organizational structure and strategies are central to CRM, data is the pivotal dimension around which the concept revolves in contemporary terms. Consequently, this chapter seeks to illustrate how the processes associated with data management, namely: data collection, data collation, data storage and data mining, are essential components of CRM in both theoretical and practical terms.

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Privacy and Confidentiality Issues in Data Mining

Information Security and Ethics ◽

10.4018/978-1-59904-937-3.ch045 ◽

2008 ◽

pp. 589-595

Author(s):

Yücel Saygin

Keyword(s):

Data Mining ◽

New York ◽

Data Collection ◽

New York Times ◽

Computer Assisted ◽

Terrorist Organizations ◽

Confidential Data ◽

The Us ◽

Privacy And Confidentiality ◽

Mining Tools

Data regarding people and their activities have been collected over the years, which has become more pervasive with widespread usage of the Internet. Collected data usually are stored in data warehouses, and powerful data mining tools are used to turn it into competitive advantage. Besides businesses, government agencies are among the most ambitious data collectors, especially in regard to the increase of safety threats coming from global terrorist organizations. For example, CAPPS (Computer Assisted Passenger Prescreening System) collects flight reservation information as well as commercial information about passengers. This data, in turn, can be utilized by government security agencies. Although CAPPS represents US national data collection efforts, it also has an effect on other countries. The following sign at the KLM ticket desk in Amsterdam International Airport illustrates the international level of data collection efforts: “Please note that KLM Royal Dutch Airlines and other airlines are required by new security laws in the US and several other countries to give security customs and immigration authorities access to passenger data. Accordingly, any information we hold about you and your travel arrangements may be disclosed to the concerning authorities of these countries in your itinerary.” This is a very striking example of how the confidential data belonging to citizens of one country could be handed over to authorities of some other country via newly enforced security laws. In fact, some of the largest airline companies in the US, including American, United, and Northwest, turned over millions of passenger records to the FBI, according to the New York Times (Schwartz & Maynard, 2004).

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Problems of Data Collection for the Application of the Data Mining Methods in Analyzing Threshold Levels of Indicators of Economic Security

KnE Social Sciences ◽

10.18502/kss.v3i2.1566 ◽

2018 ◽

Vol 3 (2) ◽

pp. 369 ◽

Cited By ~ 2

Author(s):

Zhukov A. N. ◽

Leonov P.Y.

Keyword(s):

Data Mining ◽

Data Collection ◽

Economic Security ◽

Data Mining Algorithm ◽

Threshold Values ◽

Economic Stability ◽

Time Intervals ◽

Security Issues ◽

Existing Problems ◽

Collection Data

Determining threshold values of key economic security indices describing an economic situation in any country is an important stage in the assessment of the country’s economic stability. A research was undertaken to determine how this problem can be effectively solved with such Data Mining algorithm as decision trees. According to the results of the research the effectiveness of the method was proved, but only with sufficient amount of data available. However, such data collection has a number of significant problems. These problems can be attributed to the following factors: the data for the analysis are presented with varying frequency, there is no possibility to use data over longer time intervals, the lack of a common list of indicators of economic security, which are used in different countries. The purpose of this paper is to analyze the existing problems of the data collection and to submit proposals of solving them. Keywords: Economic security, Issues of data collection, Data Mining, thresholds.

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The economics of selection of mail orders Drs. Zahavi and Levin are the masterminds behind the development of AMOS, a customized predictive modeling system for the Franklin Mint in Philadelphia, and GainSmarts, a general purpose data mining system that is the two-time winner of the KDD-CUP competition for the best data mining tools (1997 and 1998) sponsored by the American Association for Artificial Intelligence.

Journal of Interactive Marketing ◽

10.1002/dir.1016.abs ◽

2001 ◽

Vol 15 (3) ◽

pp. 53

Author(s):

Nissan Levin ◽

Jacob Zahavi

Keyword(s):

Artificial Intelligence ◽

Data Mining ◽

Predictive Modeling ◽

American Association ◽

General Purpose ◽

Mining System ◽

Data Mining System ◽

Mining Tools ◽

Selection Of

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UPAYA MENINGKATKAN KOMPETENSI GURU SMP DALAM MENYUSUN TES HASIL BELAJAR BERBASIS KETERAMPILAN BERPIKIR KRITIS MELALUI SUPERVISI AKADEMIK

JURNAL PAJAR (Pendidikan dan Pengajaran) ◽

10.33578/pjr.v3i4.7518 ◽

2019 ◽

Vol 3 (4) ◽

pp. 772

Author(s):

Leni Suryani

Keyword(s):

Critical Thinking ◽

Data Collection ◽

Learning Outcomes ◽

Student Learning Outcomes ◽

Thinking Skills ◽

Critical Thinking Skills ◽

Teacher Competence ◽

Collection Data ◽

High Level ◽

Teacher Data

This research is motivated by the competence of teachers in preparing poor learning outcomes tests and has not been able to measure high-level thinking skills, especially critical thinking skills. Therefore the researcher seeks to improve teacher competence in compiling tests on student learning outcomes based on critical thinking skills through academic supervision. This study uses a school action research design that has stages of planning, implementation, observation, and reflection. This research was conducted for 2 months starting April 9 to May 17, 2019 for Physics teachers in the 7 target schools. Data is sourced from interviews with teachers and test documents prepared by the teacher. Data collection techniques include observation, interviews and documentation. Data analysis through the stages of data collection, data simplification, data presentation, conclusion drawing. Data were analyzed using assessment rubrics adjusted to indicators of critical thinking skills. The results of this study conclude that teacher competence in preparing tests of learning outcomes based on critical thinking skills has increased from the first cycle with a percentage of 61% with sufficient categories to 76% with good categories in cycle II.

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ANALISIS PERANGKAT PEMBELAJARAN GURU PENDIDIKAN AGAMA ISLAM BERDASARKAN KURIKULUM 2013 DI SMP NEGERI 1 PERCUT SEI TUAN DELI SERDANG

ANSIRU PAI : Pengembangan Profesi Guru Pendidikan Agama Islam ◽

10.30821/ansiru.v3i2.5850 ◽

2019 ◽

Vol 3 (2) ◽

pp. 62

Author(s):

Nur Aini

Keyword(s):

Data Collection ◽

Religious Education ◽

Data Reduction ◽

Qualitative Approach ◽

Implementation Plan ◽

Analysis Technique ◽

Collection Data

The purpose of this study was to determine: (1) Suitability of 2013 Curriculum Annual Program Preparation, (2) Suitability of Compilation of the 2013 Curriculum Semester Program. (3) Appropriate components of the Learning Implementation Plan (RPP) based on Permendikbud No.22 2016. The approach used in this study is a qualitative approach The data analysis technique used is data collection, data reduction and data presentation conclusions. The technique of guaranteeing the validity of the data is done by checking trust, checking examination and checking dependency. The results of the study can be concluded that the results of the Analysis of Suitability of Annual Programming, Semester Program, and Learning Implementation Plan can be categorized as "In Accordance" because the results are obtained based on the scores of the Annual Program, Semester Program and Learning Implementation Plan (RPP) compiled by the teacher Islamic religious education in SMP Negeri 1 Percut Sei Tuan Deli Serdang.

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