Bibliografie tematiche / Time series search

Letteratura scientifica selezionata sul tema "Time series search"

Autore: Grafiati
Pubblicato: 8 giugno 2024

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  2. Tesi
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  4. Capitoli di libri
  5. Atti di convegni
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Articoli di riviste sul tema "Time series search":

1

Folgado, Duarte, Marília Barandas, Margarida Antunes, Maria Lua Nunes, Hui Liu, Yale Hartmann, Tanja Schultz e Hugo Gamboa. "TSSEARCH: Time Series Subsequence Search Library". SoftwareX 18 (giugno 2022): 101049. http://dx.doi.org/10.1016/j.softx.2022.101049.

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2

Luu, Do Ngoc, Nguyen Ngoc Phien e Duong Tuan Anh. "Tuning Parameters in Deep Belief Networks for Time Series Prediction through Harmony Search". International Journal of Machine Learning and Computing 11, n. 4 (agosto 2021): 274–80. http://dx.doi.org/10.18178/ijmlc.2021.11.4.1047.

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Abstract (sommario):
There have been several researches of applying Deep Belief Networks (DBNs) to predict time series data. Most of these works pointed out that DBNs can bring out better prediction accuracy than traditional Artificial Neural Networks. However, one of the main shortcomings of using DBNs in time series prediction concerns with the proper selection of their parameters. In this paper, we investigate the use of Harmony Search algorithm for determining the parameters of DBN in forecasting time series. Experimental results on several synthetic and real world time series datasets revealed that the DBN with parameters selected by Harmony Search performs better than the DBN with parameters selected by Particle Swarm Optimization (PSO) or random method in most of the tested datasets.
3

PRATT, KEVIN B., e EUGENE FINK. "SEARCH FOR PATTERNS IN COMPRESSED TIME SERIES". International Journal of Image and Graphics 02, n. 01 (gennaio 2002): 89–106. http://dx.doi.org/10.1142/s0219467802000482.

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Abstract (sommario):
We describe a technique for fast compression of time series, indexing of compressed series, and retrieval of series similar to a given pattern. The compression procedure identifies "important" points of a series and discards the other points. We use the important points not only for compression, but also for indexing a database of time series. Experiments show the effectiveness of this technique for indexing of stock prices, weather data and electroencephalograms.
4

SHIN, MIN-SU, e YONG-IK BYUN. "EFFICIENT PERIOD SEARCH FOR TIME SERIES PHOTOMETRY". Journal of The Korean Astronomical Society 37, n. 2 (1 giugno 2004): 79–85. http://dx.doi.org/10.5303/jkas.2004.37.2.079.

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5

Ibrahim, Ibrahim A., e Abdullah M. Albarrak. "Correlation-based search for time series data". International Journal of Computer Applications in Technology 62, n. 2 (2020): 158. http://dx.doi.org/10.1504/ijcat.2020.10026419.

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Ibrahim, A., e Abdullah M. Albarrak. "Correlation-based search for time series data". International Journal of Computer Applications in Technology 62, n. 2 (2020): 158. http://dx.doi.org/10.1504/ijcat.2020.104684.

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7

Luo, Wei, Marcus Gallagher e Janet Wiles. "Parameter-Free Search of Time-Series Discord". Journal of Computer Science and Technology 28, n. 2 (marzo 2013): 300–310. http://dx.doi.org/10.1007/s11390-013-1330-8.

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8

Huang, Silu, Erkang Zhu, Surajit Chaudhuri e Leonhard Spiegelberg. "T-Rex: Optimizing Pattern Search on Time Series". Proceedings of the ACM on Management of Data 1, n. 2 (13 giugno 2023): 1–26. http://dx.doi.org/10.1145/3589275.

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Abstract (sommario):
Pattern search is an important class of queries for time series data. Time series patterns often match variable-length segments with a large search space, thereby posing a significant performance challenge. The existing pattern search systems, for example, SQL query engines supporting MATCH_RECOGNIZE, are ineffective in pruning the large search space of variable-length segments. In many cases, the issue is due to the use of a restrictive query language modeled on time series points and a computational model that limits search space pruning. We built T-ReX to address this problem using two main building blocks: first, a MATCH_RECOGNIZE language extension that exposes the notion of segment variable and adds new operators, lending itself to better optimization; second, an executor capable of pruning the search space of matches and minimizing total query time using an optimizer. We conducted experiments using 5 real-world datasets and 11 query templates, including those from existing works. T-ReX outperformed an optimized NFA-based pattern search executor by 6x in median query time and an optimized tree-based executor by 19X.
9

Xiaoling WANG, e Clement H. C. LEUNG. "Representing Image Search Performance Using Time Series Models". International Journal of Advancements in Computing Technology 2, n. 4 (31 ottobre 2010): 140–50. http://dx.doi.org/10.4156/ijact.vol2.issue4.15.

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Liabotis, Ioannis, Babis Theodoulidis e Mohamad Saraaee. "Improving Similarity Search in Time Series Using Wavelets". International Journal of Data Warehousing and Mining 2, n. 2 (aprile 2006): 55–81. http://dx.doi.org/10.4018/jdwm.2006040103.

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Ti possono interessare anche gli elenchi estesi di opere sul tema "Time series search":
Articoli di riviste Tesi Libri

Tesi sul tema "Time series search":

1

Barsk, Viktor. "Time Series Search Using Traits". Thesis, Umeå universitet, Institutionen för datavetenskap, 2016. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-128580.

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Abstract (sommario):
Time series data occurs in many real world applications. For examplea system might have a database with a large number of time series, and a user could have a query like Find all stocks tha tbehave ”similarly” to stock A. The meaning of ”similarly” can vary between different users, use cases and domains. The goal of this thesis is to develop a method for time series search that can search based on domain specific patterns. We call these domain specific patterns traits. We have chosen to apply a trait based approach on top of a interest point based search method. First the search is conducted using a interest point method and then the results are ranked using the traits. The traits are extracted from sections of the time series and converted to a string representing its structure. The strings are then compared using Levenshtein distance to rank the search results. We have developed two types of traits. The new time series search method can be useful in many applications where a user is not looking for point-wise similarity, but rather looks at the general structure and some specific patterns. Using a trait based approach can better translate to how a user perceives time series search. The method can also yield more relevant results, since this new method can find results that a classic point-wise based search would rule out.
2

Xia, Betty Bin. "Similarity search in time series data sets". Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp04/mq24275.pdf.

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3

Bodwick, M. K. "Multivariate time series : The search for structure". Thesis, Lancaster University, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.233978.

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4

Ahsan, Ramoza. "Time Series Data Analytics". Digital WPI, 2019. https://digitalcommons.wpi.edu/etd-dissertations/529.

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Abstract (sommario):
Given the ubiquity of time series data, and the exponential growth of databases, there has recently been an explosion of interest in time series data mining. Finding similar trends and patterns among time series data is critical for many applications ranging from financial planning, weather forecasting, stock analysis to policy making. With time series being high-dimensional objects, detection of similar trends especially at the granularity of subsequences or among time series of different lengths and temporal misalignments incurs prohibitively high computation costs. Finding trends using non-metric correlation measures further compounds the complexity, as traditional pruning techniques cannot be directly applied. My dissertation addresses these challenges while meeting the need to achieve near real-time responsiveness. First, for retrieving exact similarity results using Lp-norm distances, we design a two-layered time series index for subsequence matching. Time series relationships are compactly organized in a directed acyclic graph embedded with similarity vectors capturing subsequence similarities. Powerful pruning strategies leveraging the graph structure greatly reduce the number of time series as well as subsequence comparisons, resulting in a several order of magnitude speed-up. Second, to support a rich diversity of correlation analytics operations, we compress time series into Euclidean-based clusters augmented by a compact overlay graph encoding correlation relationships. Such a framework supports a rich variety of operations including retrieving positive or negative correlations, self correlations and finding groups of correlated sequences. Third, to support flexible similarity specification using computationally expensive warped distance like Dynamic Time Warping we design data reduction strategies leveraging the inexpensive Euclidean distance with subsequent time warped matching on the reduced data. This facilitates the comparison of sequences of different lengths and with flexible alignment still within a few seconds of response time. Comprehensive experimental studies using real-world and synthetic datasets demonstrate the efficiency, effectiveness and quality of the results achieved by our proposed techniques as compared to the state-of-the-art methods.
5

Bardwell, Lawrence. "Efficient search methods for high dimensional time-series". Thesis, Lancaster University, 2018. http://eprints.lancs.ac.uk/89685/.

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Abstract (sommario):
This thesis looks at developing efficient methodology for analysing high dimensional time-series, with an aim of detecting structural changes in the properties of the time series that may affect only a subset of dimensions. Firstly, we develop a Bayesian approach to analysing multiple time-series with the aim of detecting abnormal regions. These are regions where the properties of the data change from some normal or baseline behaviour. We allow for the possibility that such changes will only be present in a, potentially small, subset of the time-series. A motivating application for this problem comes from detecting copy number variation (CNVs) in genetics, using data from multiple individuals. Secondly, we present a novel approach to detect sets of most recent changepoints in panel data which aims to pool information across time-series, so that we preferentially infer a most recent change at the same time point in multiple series. Lastly, an approach to fit a sequence of piece-wise linear segments to a univariate time series is considered. Two additional constraints on the resulting segmentation are imposed which are practically useful: (i) we require that the segmentation is robust to the presence of outliers; (ii) that there is an enforcement of continuity between the linear segments at the changepoint locations. These constraints add significantly to the computational complexity of the resulting recursive solution. Several steps are investigated to reduce the computational burden.
6

Schäfer, Patrick. "Scalable time series similarity search for data analytics". Doctoral thesis, Humboldt-Universität zu Berlin, Mathematisch-Naturwissenschaftliche Fakultät, 2015. http://dx.doi.org/10.18452/17338.

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Abstract (sommario):
Eine Zeitreihe ist eine zeitlich geordnete Folge von Datenpunkten. Zeitreihen werden typischerweise über Sensormessungen oder Experimente erfasst. Sensoren sind so preiswert geworden, dass sie praktisch allgegenwärtig sind. Während dadurch die Menge an Zeitreihen regelrecht explodiert, lag der Schwerpunkt der Forschung in den letzten Jahrzehnten auf der Analyse von (a) vorgefilterten und (b) kleinen Zeitreihendatensätzen. Die Analyse realer Zeitreihendatensätze wirft zwei Probleme auf: Erstens setzen aktuelle Ähnlichkeitsmodelle eine Vorfilterung der Zeitreihen voraus. Das beinhaltet die Extraktion charakteristischer Teilsequenzen und das Entfernen von Rauschen. Diese Vorverarbeitung muss durch einen Spezialisten erfolgen. Sie kann zeit- und kostenintensiver als die anschließende Analyse und für große Datensätze unrentabel werden. Zweitens führte die Verbesserung der Genauigkeit aktueller Ähnlichkeitsmodelle zu einem unverhältnismäßig hohen Anstieg der Komplexität (quadratisch bis biquadratisch). Diese Dissertation behandelt beide Probleme. Es wird eine symbolische Zeitreihenrepräsentation vorgestellt. Darauf aufbauend werden drei verschiedene Ähnlichkeitsmodelle eingeführt. Diese erweitern den aktuellen Stand der Forschung insbesondere dadurch, dass sie vorverarbeitungsfrei, unempfindlich gegenüber Rauschen und skalierbar sind. Anhand von 91 realen Datensätzen und Benchmarkdatensätzen wird zusätzlich gezeigt, dass die hier eingeführten Modelle auf den meisten Datenätzen die höchste Genauigkeit im Vergleich zu 15 aktuellen Ähnlichkeitsmodellen liefern. Sie sind teilweise drei Größenordnungen schneller und benötigen kaum Vorfilterung.
A time series is a collection of values sequentially recorded from sensors or live observations over time. Sensors for recording time series have become cheap and omnipresent. While data volumes explode, research in the field of time series data analytics has focused on the availability of (a) pre-processed and (b) moderately sized time series datasets in the last decades. The analysis of real world datasets raises two major problems: Firstly, state-of-the-art similarity models require the time series to be pre-processed. Pre-processing aims at extracting approximately aligned characteristic subsequences and reducing noise. It is typically performed by a domain expert, may be more time consuming than the data mining part itself, and simply does not scale to large data volumes. Secondly, time series research has been driven by accuracy metrics and not by reasonable execution times for large data volumes. This results in quadratic to biquadratic computational complexities of state-of-the-art similarity models. This dissertation addresses both issues by introducing a symbolic time series representation and three different similarity models. These contribute to state of the art by being pre-processing-free, noise-robust, and scalable. Our experimental evaluation on 91 real-world and benchmark datasets shows that our methods provide higher accuracy for most datasets when compared to 15 state-of-the-art similarity models. Meanwhile they are up to three orders of magnitude faster, require less pre-processing for noise or alignment, or scale to large data volumes.
7

Mitchell, F. "Painless knowledge acquisition for time series data". Thesis, University of Aberdeen, 1997. http://digitool.abdn.ac.uk/R?func=search-advanced-go&find_code1=WSN&request1=AAIU100889.

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Abstract (sommario):
Knowledge Acquisition has long been acknowledged as the bottleneck in producing Expert Systems. This is because, until relatively recently, the KA (Knowledge Acquisition) process has concentrated on extracting knowledge from a domain expert, which is a very time consuming process. Support tools have been constructed to help this process, but these have not been able to reduce the time radically. However, in many domains, the expert is not the only source of knowledge, nor indeed the best source of knowledge. This is particularly true in industrial settings where performance information is routinely archived. This information, if processed correctly, can provide a substantial part of the knowledge required to build a KB (Knowledge Base). In this thesis I discuss current KA approaches and then go on to outline a methodology which uses KD (Knowledge Discovery) techniques to mine archived time series data to produce fault detection and diagnosis KBs with minimal expert input. This methodology is implemented in the TIGON system, which is the focus of this thesis. TIGON uses archived information (in TIGON's case the information is from a gas turbine engine) along with guidance from the expert to produce KBs for detecting and diagnosing faults in a gas turbine engine. TIGON's performance is also analysed in some detail. A comparison with other related work is also included.
8

Charapko, Aleksey. "Time Series Similarity Search in Distributed Key-Value Data Stores Using R-Trees". UNF Digital Commons, 2015. http://digitalcommons.unf.edu/etd/565.

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Abstract (sommario):
Time series data are sequences of data points collected at certain time intervals. The advance in mobile and sensor technologies has led to rapid growth in the available amount of time series data. The ability to search large time series data sets can be extremely useful in many applications. In healthcare, a system monitoring vital signals can perform a search against the past data and identify possible health threatening conditions. In engineering, a system can analyze performances of complicated equipment and identify possible failure situations or needs of maintenance based on historical data. Existing search methods for time series data are limited in many ways. Systems utilizing memory-bound or disk-bound indexes are restricted by the resources of a single machine or hard drive. Systems that do not use indexes must search through the entire database whenever a search is requested. The proposed system uses multidimensional index in the distributed storage environment to break the bound of one physical machine and allow for high data scalability. Utilizing an index allows the system to locate the patterns similar to the query without having to examine the entire dataset, which can significantly reduce the amount of computing resources required. The system uses an Apache HBase distributed key-value database to store the index and time series data across a cluster of machines. Evaluations were conducted to examine the system’s performance using synthesized data up to 30 million data points. The evaluation results showed that, despite some drawbacks inherited from an R-tree data structure, the system can efficiently search and retrieve patterns in large time series datasets.
9

Muhammad, Fuad Muhammad Marwan. "Similarity Search in High-dimensional Spaces with Applications to Time Series Data Mining and Information Retrieval". Phd thesis, Université de Bretagne Sud, 2011. http://tel.archives-ouvertes.fr/tel-00619953.

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Abstract (sommario):
Nous présentons l'un des principaux problèmes dans la recherche d'informations et de data mining, ce qui est le problème de recherche de similarité. Nous abordons ce problème dans une perspective essentiellement métrique. Nous nous concentrons sur des données de séries temporelles, mais notre objectif général est de développer des méthodes et des algorithmes qui peuvent être étendus aux autres types de données. Nous étudions de nouvelles méthodes pour traiter le problème de recherche de similarité dans des espaces haut-dimensionnels. Les nouvelles méthodes et algorithmes que nous introduisons sont largement testés et ils montrent une supériorité sur les autres méthodes et algorithmes dans la littérature.
10

Schäfer, Patrick [Verfasser], Alexander [Akademischer Betreuer] Reinefeld, Ulf [Akademischer Betreuer] Leser e Artur [Akademischer Betreuer] Andrzejak. "Scalable time series similarity search for data analytics / Patrick Schäfer. Gutachter: Alexander Reinefeld ; Ulf Leser ; Artur Andrzejak". Berlin : Mathematisch-Naturwissenschaftliche Fakultät, 2015. http://d-nb.info/1078309620/34.

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Libri sul tema "Time series search":

1

Fuentes, Andreas. The determinants of on-the-job search: A time series analysis for Britain. Oxford: Oxford University, Institute of Economics and Statistics, 1998.

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2

Perotti, Roberto. In search of the transmission mechanism of fiscal policy. Cambridge, Mass: National Bureau of Economic Research, 2007.

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3

Marie, Robertson Eleanor. The search. New York, N.Y: G.P. Putnam's Sons, 2010.

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4

Marie, Robertson Eleanor. The search. New York: G.P. Putnam's Sons, 2010.

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5

Marie, Robertson Eleanor. The Search. New York: Penguin USA, Inc., 2010.

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6

Marie, Robertson Eleanor. Opasnyĭ sled. Moskva: Ėksmo, 2011.

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Marie, Robertson Eleanor. De zoektocht. Amsterdam: Boekerij, 2013.

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8

Larson, Erik. The devil in the white city: Murder, magic, and madness at the fair that changed America. New York: Crown Publishers, 2003.

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Larson, Erik. The devil in the white city: Murder, magic, and madness at the fair that changed America. Waterville, Me: Thorndike Press, 2003.

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Larson, Erik. Bai cheng e mo. 8a ed. Beijing Shi: Ren min wen xue chu ban she, 2010.

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Capitoli di libri sul tema "Time series search":

1

Schwarzenberg-Czerny, Alex. "Period Search". In Astronomical Time Series, 183–86. Dordrecht: Springer Netherlands, 1997. http://dx.doi.org/10.1007/978-94-015-8941-3_19.

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2

Sperandio, Ricardo Carlini, Simon Malinowski, Laurent Amsaleg e Romain Tavenard. "Time Series Retrieval Using DTW-Preserving Shapelets". In Similarity Search and Applications, 257–70. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-02224-2_20.

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Shasha, Dennis, e Yunyue Zhu. "Flexible Similarity Search". In High Performance Discovery in Time Series, 87–100. New York, NY: Springer New York, 2004. http://dx.doi.org/10.1007/978-1-4757-4046-2_4.

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Karamitopoulos, Leonidas, Georgios Evangelidis e Dimitris Dervos. "PCA-based Time Series Similarity Search". In Annals of Information Systems, 255–76. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-1-4419-1280-0_11.

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Aßfalg, Johannes, Hans-Peter Kriegel, Peer Kröger e Matthias Renz. "Probabilistic Similarity Search for Uncertain Time Series". In Lecture Notes in Computer Science, 435–43. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02279-1_31.

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Kashyap, Shrikant, Mong Li Lee e Wynne Hsu. "Similar Subsequence Search in Time Series Databases". In Lecture Notes in Computer Science, 232–46. Berlin, Heidelberg: Springer Berlin Heidelberg, 2011. http://dx.doi.org/10.1007/978-3-642-23088-2_16.

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Sanchez, Heider, e Benjamin Bustos. "Anomaly Detection in Streaming Time Series Based on Bounding Boxes". In Similarity Search and Applications, 201–13. Cham: Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-11988-5_19.

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Movchan, Aleksandr, e Mikhail Zymbler. "Time Series Subsequence Similarity Search Under Dynamic Time Warping Distance on the Intel Many-core Accelerators". In Similarity Search and Applications, 295–306. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-25087-8_28.

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von Landesberger, Tatiana, Viktor Voss e Jörn Kohlhammer. "Semantic Search and Visualization of Time-Series Data". In Studies in Computational Intelligence, 205–16. Berlin, Heidelberg: Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-642-02184-8_14.

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Choy, Murphy, e Ma Nang Laik. "Intelligent Time Series Forecasting Through Neighbourhood Search Heuristics". In Advances in Intelligent Systems and Computing, 434–44. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-03405-4_30.

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Atti di convegni sul tema "Time series search":

1

Buono, Paolo, Aleks Aris, Catherine Plaisant, Amir Khella e Ben Shneiderman. "Interactive pattern search in time series". In Electronic Imaging 2005, a cura di Robert F. Erbacher, Jonathan C. Roberts, Matti T. Grohn e Katy Borner. SPIE, 2005. http://dx.doi.org/10.1117/12.587537.

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Hsieh, Tsung-Yu, Suhang Wang, Yiwei Sun e Vasant Honavar. "Explainable Multivariate Time Series Classification". In WSDM '21: The Fourteenth ACM International Conference on Web Search and Data Mining. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3437963.3441815.

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Rakhshani, Hojjat, Hassan Ismail Fawaz, Lhassane Idoumghar, Germain Forestier, Julien Lepagnot, Jonathan Weber, Mathieu Brevilliers e Pierre-Alain Muller. "Neural Architecture Search for Time Series Classification". In 2020 International Joint Conference on Neural Networks (IJCNN). IEEE, 2020. http://dx.doi.org/10.1109/ijcnn48605.2020.9206721.

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Karamitopoulos, Leonidas, e Georgios Evangelidis. "Cluster-Based Similarity Search in Time Series". In 2009 Fourth Balkan Conference in Informatics. IEEE, 2009. http://dx.doi.org/10.1109/bci.2009.22.

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Charisi, Amalia, Fragkiskos D. Malliaros, Evangelia I. Zacharaki e Vasileios Megalooikonomou. "Multiresolution similarity search in time series data". In the 6th International Conference. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2504335.2504370.

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Peng, Jinglin, Hongzhi Wang, Jianzhong Li e Hong Gao. "Set-based Similarity Search for Time Series". In SIGMOD/PODS'16: International Conference on Management of Data. New York, NY, USA: ACM, 2016. http://dx.doi.org/10.1145/2882903.2882963.

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Zhang, Chuanlei, Ji'an Luo, Shanwen Zhang e Chen Zhang. "Introduction to time series search engine systems". In 2012 International Conference on Systems and Informatics (ICSAI). IEEE, 2012. http://dx.doi.org/10.1109/icsai.2012.6223532.

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Wang, Shiyu. "NeuralReconciler for Hierarchical Time Series Forecasting". In WSDM '24: The 17th ACM International Conference on Web Search and Data Mining. New York, NY, USA: ACM, 2024. http://dx.doi.org/10.1145/3616855.3635806.

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Wi, Hyowon, Yehjin Shin e Noseong Park. "Continuous-time Autoencoders for Regular and Irregular Time Series Imputation". In WSDM '24: The 17th ACM International Conference on Web Search and Data Mining. New York, NY, USA: ACM, 2024. http://dx.doi.org/10.1145/3616855.3635831.

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Hayran, Ahmet, Hasan Ogul e Esma Ozkoc. "Content-Based Search on Time-Series Microarray Databases". In 2014 25th International Workshop on Database and Expert Systems Applications (DEXA). IEEE, 2014. http://dx.doi.org/10.1109/dexa.2014.33.

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Rapporti di organizzazioni sul tema "Time series search":

1

Audoly, Richard. Firm Dynamics and Random Search over the Business Cycle. Federal Reserve Bank of New York, agosto 2023. http://dx.doi.org/10.59576/sr.1069.

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Abstract (sommario):
I build a tractable random search model with firm dynamics, on-the-job search, and aggregate shocks. Multi-worker firms make recruitment decisions, choose whether to enter or exit the market, and design wage contracts. Tractability is obtained by showing that, under a set of assumptions on the recruitment technology, the decisions of workers and firms can be expressed in terms of the firms’ current productivity. I introduce a numerical solution method to accommodate aggregate shocks in this environment and show that the model can replicate salient features of both firm-level data on productivity and employment and aggregate time series describing the business cycle. I use this framework to quantify the drivers of worker reallocation over the recent business cycle in Britain.
2

Rosen, Michael, C. Matthew Stewart, Hadi Kharrazi, Ritu Sharma, Montrell Vass, Allen Zhang e Eric B. Bass. Potential Harms Resulting From Patient-Clinician Real-Time Clinical Encounters Using Video-based Telehealth: A Rapid Evidence Review. Agency for Healthcare Research and Quality (AHRQ), settembre 2023. http://dx.doi.org/10.23970/ahrqepc_mhs4telehealth.

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Objectives. To review the evidence on harms associated with patient-clinician real time encounters using video-based telehealth and determine the effectiveness of any related patient safety practices (PSPs). PSPs are interventions, strategies, or approaches intended to prevent or mitigate unintended consequences of healthcare delivery and improve patient safety. This review provides information that clinicians and health system leaders need to determine how to minimize harms from increasing real-time use of telehealth. Methods. We followed rapid review processes of the Agency for Healthcare Research and Quality Evidence-based Practice Center Program. We searched PubMed, EMBASE, and Cochrane to identify eligible studies published from 2012 to 2022, supplemented by a search for unpublished evaluations and white papers. Outcomes of interest included: adverse events (any harm to patients due to medical care), other specified harms (i.e., preventable hospitalizations, inappropriate treatment, missed or delayed diagnoses, duplication of services, privacy breaches), and implementation factors for any PSPs. Findings. Our search retrieved 7,155 citations, of which 23 studies (including 6 randomized controlled trials [RCTs]) were eligible for review. Fourteen studies reported on adverse events or unintended effects of telehealth; these studies were conducted in diverse settings, with four studies in behavioral health, two each in rehabilitation, transplant, and Parkinson’s care, and one each in postoperative, termination of pregnancy, community health, and hospital-at-home settings. Adverse events such as death, reoperation, infection, or major complications were infrequent in both telehealth and usual care groups, making it difficult to find statistically significant differences. One RCT found telehealth resulted in fewer medication errors than standard care. Thirteen studies examined preventable hospitalizations or emergency department (ED) visits and reported mixed findings; six of these studies were in postoperative care and two were in urological care. Of the 6 RCTs, 3 showed no difference in risk of hospitalization or ED visits for telehealth compared to usual care, and 3 showed reduced risk for patients receiving telehealth. We found no studies on the effectiveness of PSPs in reducing harms associated with real-time telehealth. Conclusions. Studies have evaluated the frequency and severity of harms associated with real-time video-based telehealth encounters between clinicians and patients, examining a variety of patient safety measures. Telehealth was not inferior to usual care in terms of hospitalizations or ED visits. No studies evaluated a specific PSP. More research is needed to improve understanding of harms associated with real-time use of telehealth and how to prevent or mitigate those harms.
3

Parsons, Helen M., Hamdi I. Abdi, Victoria A. Nelson, Amy M. Claussen, Brittin L. Wagner, Karim T. Sadak, Peter B. Scal, Timothy J. Wilt e Mary Butler. Transitions of Care From Pediatric to Adult Services for Children With Special Healthcare Needs. Agency for Healthcare Research and Quality (AHRQ), maggio 2022. http://dx.doi.org/10.23970/ahrqepccer255.

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Objective. To understand the evidence base for care interventions, implementation strategies, and between-provider communication tools among children with special healthcare needs (CSHCN) transitioning from pediatric to adult medical care services. Data sources. We searched Ovid MEDLINE, Ovid Embase, the Cochrane Central trials (CENTRAL) registry, and CINAHL to identify studies through September 10, 2021. We conducted grey literature searches to identify additional resources relevant to contextual questions. Review methods. Using a mixed-studies review approach, we searched for interventions or implementation strategies for transitioning CSHCN from pediatric to adult services. Two investigators screened abstracts and full-text articles of identified references for eligibility. Eligible studies included randomized controlled trials, quasi-experimental observational studies, and mixed-method studies of CSHCN, their families, caregivers, or healthcare providers. We extracted basic study information from all eligible studies and grouped interventions into categories based on disease conditions. We summarized basic study characteristics for included studies and outcomes for studies assessed as low to medium risk of bias using RoB-2. Results. We identified 9,549 unique references, 440 of which represented empirical research; of these, 154 (16 major disease categories) described or examined a care transition intervention with enough detail to potentially be eligible for inclusion in any of the Key Questions. Of these, 96 studies met comparator criteria to undergo risk of bias assessment; however only 9 studies were assessed as low or medium risk of bias and included in our analytic set. Low-strength evidence shows transition clinics may not improve hemoglobin A1C levels either at 12 or 24 months in youth with type 1 diabetes mellitus compared with youth who received usual care. For all other interventions and outcomes, the evidence was insufficient to draw meaningful conclusions because the uncertainty of evidence was too high. Some approaches to addressing barriers include dedicating time and resources to support transition planning, developing a workforce trained to care for the needs of this population, and creating structured processes and tools to facilitate the transition process. No globally accepted definition for effective transition of care from pediatric to adult services for CSHCN exists; definitions are often drawn from principles for transitions, encompassing a broad set of clinical aspects and other factors that influence care outcomes or promote continuity of care. There is also no single measure or set of measures consistently used to evaluate effectiveness of transitions of care. The literature identifies a limited number of available training and other implementation strategies focused on specific clinical specialties in targeted settings. No eligible studies measured the effectiveness of providing linguistically and culturally competent healthcare for CSHCN. Identified transition care training, and care interventions to
4

Johnson, Eric M., Robert Urquhart e Maggie O'Neil. The Importance of Geospatial Data to Labor Market Information. RTI Press, giugno 2018. http://dx.doi.org/10.3768/rtipress.2018.pb.0017.1806.

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School-to-work transition data are an important component of labor market information systems (LMIS). Policy makers, researchers, and education providers benefit from knowing how long it takes work-seekers to find employment, how and where they search for employment, the quality of employment obtained, and how steady it is over time. In less-developed countries, these data are poorly collected, or not collected at all, a situation the International Labour Organization and other donors have attempted to change. However, LMIS reform efforts typically miss a critical part of the picture—the geospatial aspects of these transitions. Few LMIS systems fully consider or integrate geospatial school-to-work transition information, ignoring data critical to understanding and supporting successful and sustainable employment: employer locations; transportation infrastructure; commute time, distance, and cost; location of employment services; and other geographic barriers to employment. We provide recently collected geospatial school-to-work transition data from South Africa and Kenya to demonstrate the importance of these data and their implications for labor market and urban development policy.
5

Quak, Evert-Jan. K4D’s Work on the Indirect Impacts of COVID-19 in Low- and Middle- Income Countries. Institute of Development Studies (IDS), giugno 2021. http://dx.doi.org/10.19088/k4d.2021.093.

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This report is not an in-depth nor exhaustive analysis of the many indirect impacts of the pandemic on LMICs. The content is purely based on the requests from FCDO to the K4D services on this topic, and as such can only give an illustrative overview of the findings from these requests. Furthermore, insights are also taken from the data that K4D collects for each request based on the information provided by advisers and FCDO (e.g. purpose of the request, adviser’s cadre), hence, the data is limited to the information available to the K4D team at the time of the request and the level of details available may vary from one request to the other. The selection of relevant K4D outputs on the pandemic’s indirect impacts was based on an extensive search in the K4D repository on titles and research questions. The Annex shows all K4D outputs included in this report. The purpose of this report is to inform FCDO about some of the specifics of their requests on the indirect impacts of COVID-19, in general. This report will also be used as input for a K4D-FCDO learning event that takes place on the 6th of July 2021. During the event learning and evidence, trends will be discussed and how evidence and learning informed decision-making on policy and programming.
6

F, Verdugo-Paiva, Acuña María Paz, Solá Iván e Rada Gabriel. Is remdesivir an effective intervention in people with acute COVID-19? Epistemonikos Interactive Evidence Synthesis, settembre 2023. http://dx.doi.org/10.30846/ies.527e413d283.p1.

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Objective This living systematic review aims to provide a timely, rigorous and continuously updated summary of the evidence available on the role of remdesivir in the treatment of patients with COVID-19 . Data sources We will conduct searches in the L·OVE (Living Overview of Evidence) platform for COVID-19, a system that maps PICO questions to a repository maintained through regular searches in electronic databases, preprint servers, trial registries and other resources relevant to COVID-19. No date or language restrictions will be applied. Eligibility criteria for selecting studies and methods We adapted an already published common protocol for multiple parallel systematic reviews to the specificities of this review. We will include randomized trials evaluating the effect of remdesivir, as monotherapy or in combination with other drugs, versus placebo or no treatment in patients with COVID-19. Two reviewers will independently screen each study for eligibility, extract data, and assess the risk of bias. We will pool the results using meta-analysis and apply the GRADE system to assess the certainty of the evidence for each outcome. A living, web-based version of this review will be openly available during the COVID-19 pandemic. We will resubmit it every time the conclusions change or whenever there are substantial updates. Ethics and dissemination No ethics approval is considered necessary. The results of this review will be widely disseminated via peer-reviewed publications, social networks, and traditional media. PROSPERO Registration CRD42020183384
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F, Verdugo-Paiva, Acuña María Paz, Solá Iván e Rada Gabriel. Is remdesivir an effective intervention in people with acute COVID-19? Epistemonikos Interactive Evidence Synthesis, settembre 2023. http://dx.doi.org/10.30846/ies.527e413d282.v1.

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Abstract (sommario):
Objective This living systematic review aims to provide a timely, rigorous and continuously updated summary of the evidence available on the role of remdesivir in the treatment of patients with COVID-19 . Data sources We will conduct searches in the L·OVE (Living Overview of Evidence) platform for COVID-19, a system that maps PICO questions to a repository maintained through regular searches in electronic databases, preprint servers, trial registries and other resources relevant to COVID-19. No date or language restrictions will be applied. Eligibility criteria for selecting studies and methods We adapted an already published common protocol for multiple parallel systematic reviews to the specificities of this review. We will include randomized trials evaluating the effect of remdesivir, as monotherapy or in combination with other drugs, versus placebo or no treatment in patients with COVID-19. Two reviewers will independently screen each study for eligibility, extract data, and assess the risk of bias. We will pool the results using meta-analysis and apply the GRADE system to assess the certainty of the evidence for each outcome. A living, web-based version of this review will be openly available during the COVID-19 pandemic. We will resubmit it every time the conclusions change or whenever there are substantial updates. Ethics and dissemination No ethics approval is considered necessary. The results of this review will be widely disseminated via peer-reviewed publications, social networks, and traditional media. PROSPERO Registration CRD42020183384
8

F, Verdugo-Paiva, Acuña M, Solá I e Rada G. Is remdesivir an effective intervention in people with acute COVID-19? Epistemonikos Interactive Evidence Synthesis, settembre 2023. http://dx.doi.org/10.30846/ies.527e413d28.v1.

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Abstract (sommario):
Objective This living systematic review aims to provide a timely, rigorous and continuously updated summary of the evidence available on the role of remdesivir in the treatment of patients with COVID-19 . Data sources We will conduct searches in the L·OVE (Living Overview of Evidence) platform for COVID-19, a system that maps PICO questions to a repository maintained through regular searches in electronic databases, preprint servers, trial registries and other resources relevant to COVID-19. No date or language restrictions will be applied. Eligibility criteria for selecting studies and methods We adapted an already published common protocol for multiple parallel systematic reviews to the specificities of this review. We will include randomized trials evaluating the effect of remdesivir, as monotherapy or in combination with other drugs, versus placebo or no treatment in patients with COVID-19. Two reviewers will independently screen each study for eligibility, extract data, and assess the risk of bias. We will pool the results using meta-analysis and apply the GRADE system to assess the certainty of the evidence for each outcome. A living, web-based version of this review will be openly available during the COVID-19 pandemic. We will resubmit it every time the conclusions change or whenever there are substantial updates. Ethics and dissemination No ethics approval is considered necessary. The results of this review will be widely disseminated via peer-reviewed publications, social networks, and traditional media. PROSPERO Registration CRD42020183384
9

F, Verdugo-Paiva, Acuña M, Solá I e Rada G. Is remdesivir an effective intervention in people with acute COVID-19? Epistemonikos Interactive Evidence Synthesis, settembre 2023. http://dx.doi.org/10.30846/ies.527e413d28.

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Abstract (sommario):
Objective This living systematic review aims to provide a timely, rigorous and continuously updated summary of the evidence available on the role of remdesivir in the treatment of patients with COVID-19 . Data sources We will conduct searches in the L·OVE (Living Overview of Evidence) platform for COVID-19, a system that maps PICO questions to a repository maintained through regular searches in electronic databases, preprint servers, trial registries and other resources relevant to COVID-19. No date or language restrictions will be applied. Eligibility criteria for selecting studies and methods We adapted an already published common protocol for multiple parallel systematic reviews to the specificities of this review. We will include randomized trials evaluating the effect of remdesivir, as monotherapy or in combination with other drugs, versus placebo or no treatment in patients with COVID-19. Two reviewers will independently screen each study for eligibility, extract data, and assess the risk of bias. We will pool the results using meta-analysis and apply the GRADE system to assess the certainty of the evidence for each outcome. A living, web-based version of this review will be openly available during the COVID-19 pandemic. We will resubmit it every time the conclusions change or whenever there are substantial updates. Ethics and dissemination No ethics approval is considered necessary. The results of this review will be widely disseminated via peer-reviewed publications, social networks, and traditional media. PROSPERO Registration CRD42020183384
10

KellerLynn, Katie. Redwood National and State Parks: Geologic resources inventory report. National Park Service, ottobre 2021. http://dx.doi.org/10.36967/nrr-2287676.

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Comprehensive park management to fulfill the NPS mission requires an accurate inventory of the geologic features of a park unit, but Comprehensive park management to fulfill the NPS mission requires an accurate inventory of the geologic features of a park unit, but park managers may not have the needed information, geologic expertise, or means to complete such an undertaking; therefore, the Geologic Resources Inventory (GRI) provides information and resources to help park managers make decisions for visitor safety, planning and protection of infrastructure, and preservation of natural and cultural resources. Information in the GRI report may also be useful for interpretation. park managers may not have the needed information, geologic expertise, or means to complete such an undertaking; therefore, the Geologic Resources Inventory (GRI) provides information and resources to help park managers make decisions for visitor safety, planning and protection of infrastructure, and preservation of natural and cultural resources. Information in the GRI report may also be useful for interpretation. This report synthesizes discussions from a scoping meeting for Redwood National and State Parks (referred to as the “parks” throughout this report) held in 2004 and a follow-up conference call in 2019. Two GRI–compiled GIS data sets of the geology and geohazards of the parks are the principal deliverables of the GRI. The GRI GIS data are available on the GRI publications website http://go.nps.gov/gripubs and through the NPS Integrated Resource Management Applications (IRMA) portal https://irma.nps.gov/App/Portal/Home. Enter “GRI” as the search text and select a park from the unit list. Writing of this report was based on those data and the interpretations of the source map authors (see “GRI Products” and “Acknowledgements”). A geologic map poster illustrates the geology GRI GIS data set and serves as a primary figure for this GRI report. No poster was prepared for the geohazards GRI GIS data set. Additionally, figure 7 of this report illustrates the locations of the major geologic features in the parks. Unlike the poster, which is divided into a northern and southern portion to show detail while accommodating the parks’ length, figure 7 is a single-page, simplified map. The features labeled on figure 7 are discussed in the “Geologic History, Features, and Processes” chapter. To provide a context of geologic time, this report includes a geologic time scale (see "Geologic History, Features, and Processes"). The parks’ geologic story encompasses 200 million years, starting in the Jurassic Period. Following geologic practice, the time scale is set up like a stratigraphic column, with the oldest units at the bottom and the youngest units at the top. Organized in this manner, the geologic time scale table shows the relative ages of the rock units that underlie the parks and the unconsolidated deposits that lie at the surface. Reading the “Geologic Event” column in the table, from bottom to top, will provide a chronologic order of the parks’ geologic history. The time scale includes only the map units within the parks that also appear on the geologic map poster; that is, map units of the geohazards data are not included. Geology is a complex science with many specialized terms. This report provides definitions of geologic terms at first mention, typically in parentheses following the term. Geologic units in the GRI GIS data are referenced in this report using map unit symbols; for example, map unit KJfrc stands for the Cretaceous (K) and Jurassic (J) Franciscan Complex (f), Redwood Creek schist (rc), which underlies a portion of the Redwood Creek watershed (see “GRI Products”).

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