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High Performance Discovery In Time Series
Time-series data—data arriving in time order, or a data stream—can be found in fields such as physics, finance, music, networking, and medical instrumentation. Designing fast, scalable algorithms for analyzing single or multiple time series can lead to scientific discoveries, medical diagnoses, and perhaps profits. High Performance Discovery in Time Series presents rapid-discovery techniques for finding portions of time series with many events (i.e., gamma-ray scatterings) and finding closely related time series (i.e., highly correlated price and return histories, or musical melodies). A typical time-series technique may compute a "consensus" time series—from a collection of time serie...
High Performance Discovery In Time Series
This monograph is a technical survey of concepts and techniques for describing and analyzing large-scale time-series data streams. Some topics covered are algorithms for query by humming, gamma-ray burst detection, pairs trading, and density detection. Included are self-contained descriptions of wavelets, fast Fourier transforms, and sketches as they apply to time-series analysis. Detailed applications are built on a solid scientific basis.
Monographic Series
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The Student
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Discipline and Discovery Series: Exploring Ephesians
Did you ever know how much detail is in each verse of the Bible? In this study you will find out! You will spend twelve weeks going through the book of Ephesians and finding the hidden treasure you once passed over. As you go through this study, you will read the Word, memorize scripture, and pray each day. These are some of the basic blocks of discipline you need for maturity in your walk of faith. Exploring Ephesians will ignite your the passion for the Word of God. Are you ready to put on your armor and learn God's truth? Jackie Seiferth lives in Dublin, CA with her husband, Joe and daughter, Sahara. She has been a Bible study leader and teacher for 5 years, teaching a wide range of women. She is currently enrolled in Northwestern Theological Seminary to pursue a BA/MA degree in Biblical Studies. Her passion is to study the Word of God and inspire others to become excited about what it says. In her free time she loves to snowboard, read, and go to the zoo with her daughter.
Sentiment Analysis and Knowledge Discovery in Contemporary Business
In the era of social connectedness, people are becoming increasingly enthusiastic about interacting, sharing, and collaborating through online collaborative media. However, conducting sentiment analysis on these platforms can be challenging, especially for business professionals who are using them to collect vital data. Sentiment Analysis and Knowledge Discovery in Contemporary Business is an essential reference source that discusses applications of sentiment analysis as well as data mining, machine learning algorithms, and big data streams in business environments. Featuring research on topics such as knowledge retrieval and knowledge updating, this book is ideally designed for business managers, academicians, business professionals, researchers, graduate-level students, and technology developers seeking current research on data collection and management to drive profit.
Discovery of Ill–Known Motifs in Time Series Data
This book includes a novel motif discovery for time series, KITE (ill-Known motIf discovery in Time sEries data), to identify ill-known motifs transformed by affine mappings such as translation, uniform scaling, reflection, stretch, and squeeze mappings. Additionally, such motifs may be covered with noise or have variable lengths. Besides KITE’s contribution to motif discovery, new avenues for the signal and image processing domains are explored and created. The core of KITE is an invariant representation method called Analytic Complex Quad Tree Wavelet Packet transform (ACQTWP). This wavelet transform applies to motif discovery as well as to several signal and image processing tasks. The efficiency of KITE is demonstrated with data sets from various domains and compared with state-of-the-art algorithms, where KITE yields the best outcomes.
