Order ID:89JHGSJE83839 | Style:APA/MLA/Harvard/Chicago | Pages:5-10 |
Instructions:
Data Mining and Its Relationships Sentiment Analysis and Text Mining
Go to teradatauniversitynetwork.com and look for the “eBay Analytics” case study. Read the case carefully and expand your understanding by looking up extra material on the Internet, then respond to the case questions.
Go to kdnuggets.com for more information. Examine the sections on both applications and software. Find the names of at least three more data mining and text mining packages.
Explain how data mining, text mining, and sentiment analysis are related.
Define text mining and explore its most common applications in your own terms.
What does it mean to give text-based data structure? Dissect the many approaches of instilling structure in them.
What function does natural language processing play in text mining? In the context of text mining, discuss the possibilities and limits of natural language processing (NLP).
Data Mining and Its Relationships Sentiment Analysis and Text Mining
RUBRIC |
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Excellent Quality 95-100%
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Introduction
45-41 points The background and significance of the problem and a clear statement of the research purpose is provided. The search history is mentioned. |
Literature Support 91-84 points The background and significance of the problem and a clear statement of the research purpose is provided. The search history is mentioned. |
Methodology 58-53 points Content is well-organized with headings for each slide and bulleted lists to group related material as needed. Use of font, color, graphics, effects, etc. to enhance readability and presentation content is excellent. Length requirements of 10 slides/pages or less is met. |
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Average Score 50-85% |
40-38 points More depth/detail for the background and significance is needed, or the research detail is not clear. No search history information is provided. |
83-76 points Review of relevant theoretical literature is evident, but there is little integration of studies into concepts related to problem. Review is partially focused and organized. Supporting and opposing research are included. Summary of information presented is included. Conclusion may not contain a biblical integration. |
52-49 points Content is somewhat organized, but no structure is apparent. The use of font, color, graphics, effects, etc. is occasionally detracting to the presentation content. Length requirements may not be met. |
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Poor Quality 0-45% |
37-1 points The background and/or significance are missing. No search history information is provided. |
75-1 points Review of relevant theoretical literature is evident, but there is no integration of studies into concepts related to problem. Review is partially focused and organized. Supporting and opposing research are not included in the summary of information presented. Conclusion does not contain a biblical integration. |
48-1 points There is no clear or logical organizational structure. No logical sequence is apparent. The use of font, color, graphics, effects etc. is often detracting to the presentation content. Length requirements may not be met |
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Data Mining and Its Relationships Sentiment Analysis and Text Mining |
Data Mining and Its Relationships Sentiment Analysis and Text Mining