Fluent Essays

This is continuation of IP1 and IP 2 For this IP 3, you will provide a detailed, full-sentence outline of your paper. In APA format, the full-sentence outline is essentially the same as the alphanumeric outline. The main difference (as the title suggests) is that full sentences are required at each level of the outline (Purdue University Online Writing Lab, n.d.b). Your outline should be comprised of complete sentences. Bullet points and sentence fragments are not acceptable. Your full sentence outline should detail the key sections of your paper. The following is an example of a full-sentence outline: Man-made pollution is the primary cause of global warming. Greenhouse gas emissions are widely identified by the scientific community to be harmful. The burning of coal and fossil fuels are the primary releasers of hazardous greenhouse gases. Your full-sentence outline should include the introduction, conclusion, transitions, main sections and paragraphs, and the main points and subpoints. Your full-sentence outline should also include an APA reference list on a separate page. Quotes within the outline must also utilize APA in-text citations (Purdue University Online Writing Lab, n.d.a).   References Purdue University Online Writing Lab. (n.d.a). The Purdue OWL: Sample outlines. http://owl.english.purdue.edu/media/pdf/20081113013048_544.pdf Purdue University Online Writing Lab. (n.d.b). Types of outlines and samples. http://owl.english.purdue.edu/owl/resource/544/03/Hybrid Scalable Researcher Recommendation System Using Page Rank Algorithm 1 Hybrid Scalable Researcher Recommendation System Using Page Rank Algorithm 5 Hybrid Scalable Researcher Recommendation System Using Page Rank Algorithm Dinesh Kalla Colorado Technical University CS 857: Business Intelligence Dr D Revenaugh 3rd March 2021 Problem Statement Page rank algorithm is used by Google search engine to rank websites based on their importance. Google scholar is the commonly used recommender system for research papers. The increasing number of research papers makes it difficult for novice academic researchers to obtain relevant scholarly articles with ease. The current recommender system does not have scalable functionality to cater to the increasing number of journals and articles published daily in the global arena. Other recommender systems such as Microsoft Academic, Web of Science, and PubMed databases use the collaborative approach, hindered by data protection legislation. Additionally, the said academic search engines domicile in one particular field of study. My research paper will focus on resolving this problem by recommending a hybrid scalable search engine that will utilize a page rank algorithm to determine the relevance of academic documents and display them in the order of importance. It will combine content-based and co-citation recommendations to produce related documents, including the recently published ones, without compromising the quality of recommendations. Justification / Literature Review Recommender systems have been applied in a variety of applications such as Twitter and Netflix. For instance, Twitter uses PageRank to suggest new followers to its users. To generate this suggestion, the application is designed in such a way it performs personalized PageRank by establishing two copies of each active user; a content producer and a content consumer. In this sense, a user can post a tweet or, in other cases, read a tweet by other users. A content produced by the user can be retweeted, further-reaching a new audience. This developing network can leverage on PageRank algorithm to suggest new followers. Another application scenario is in movie rental sites such as Netflix, where a user considers a movie to be relevant if other users like the movie. The second approach to like a movie is when a mutual friend likes movies that we both have interests. With these two approaches, Netflix can create a personalized ranking for users on the film they want using the PageRank algorithm. The ‘behavior’ of other mutual users on the platform enables the system to determine what other users might like. Data mining systems also utilize a similar approach where user behaviors can predict what products they might like (Bathrinath, 2019). In Business intelligence systems can track user preferences and suggest new products to the user in priority. Data mining is categorized into three groups, namely, web content minDesigning Business Intelligence System with PageRank Algorithm 5 Designing Business Intelligence System with PageRank Algorithm Dinesh Kalla CS 857 : Business Intelligence : IP 2 Colorado Technical University Dr D Revenaugh 17th March 2021 Problem Statement Organizations are continuously bombarded with vast amounts of data. Managers must gain the expertise needed to fully utilize the benefits that come with business intelligence systems (Olszak, 2016). Data mining has become an essential tool for managers that provide insights about their daily operations and leverage the information provided by decision support systems to improve customer relationships (Visinescu, 2017). Additionally, managers require business intelligence systems that can rank the output in the order of priority. PageRank algorithm can replace the traditional data mining algorithms that will be discussed in-depth in the literature review (Florescu, 2017). The purpose of this research paper is to demonstrate how the PageRank algorithm can be implemented in business intelligence (BI) systems to support managers in decision-making in hiring active authors or researchers belongs to computer science field of study by displaying query results in order of their significance in supporting hiring processes (Kanakia, 2019). Justification / Literature Review Algorithms are used in business intelligence systems to unearth patterns otherwise challenging to deduce from a data warehouse. The algorithms can generate several relationships between data and another variable. Most BI systems utilize statistical techniques to analyze and create reports used by managers to make decisions (Arnott, 2017). Examples of these algorithms include; regression analysis, decision trees, association, and cluster analysis. Companies such as Oracle, Microsoft dynamic, and SAP ERP software have business intelligence functionality (Gounder et al., 2016). SAS, a statistical tool, currently has business intelligence functionalities. Additionally, SQL Server 2005/2008 also contains business intelligence functionality to help users sieve specific information from the database server. Business intelligence systems offer more advanced reporting features than traditional statistical software; therefore, managers find it more intriguing to use data mining tools to provide reports in sequential order to support their decision-making process (Tvrdikova, 2017). As managers grapple with massive data that they use to make a decision, there is a need to rank the reports generated by BI systems based on their significant impact on business processes (Kasemsap, 2016). To have a competitive advantage and effectively run a business, there a need to rely on automated data mining tools that can support their daily activities (Oussous, 2018) Methodology In my research, I will use quantitative measures to establish which algorithms are used in various business intelligence systems and how effective they arehttp://owl.english.purdue.edu/owl/resource/544/01/ The Purdue OWL: Sample Outlines Alphanumeric Outline THE COLLEGE APPLICATION PROCESS I. CHOOSE DESIRED COLLEGES A. Visit and evaluate college campuses B. Visit and evaluate college websites 1. Look for interesting classes 2. Note important statistics II. PREPARE APPLICATION A. Write personal statement 1. Choose interesting topic a. Describe an influential person in your life (1) Favorite high school teacher (2) Grandparent b. Describe a challenging life event 2. Include important personal details a. Volunteer work b. Participation in varsity sports B. Revise personal statement III. COMPILE RÉSUMÉ A. List relevant coursework B. List work experience C. List volunteer experience 1. Tutor at foreign language summer camp 2. Counselor for suicide prevention hotline http://owl.english.purdue.edu/owl/resource/544/01/ Full Sentence Outline I. Man-made pollution is the primary cause of global warming. A. Greenhouse gas emissions are widely identified by the scientific community to be harmful. 1. The burning of coal and fossil fuels are the primary releasers of hazardous greenhouse gases. Full sentence outlines are often accompanied with an APA reference list on a separate page. Quotes within the outline must also utilize APA in-text citations. Decimal Outline 1.0 Choose Desired College 1.1 Visit and evaluate college campuses 1.2 Visit and evaluate college websites 1.2.1 Look for interesting classes 1.2.2 Note important statistics