Context Aware Recommendation Systems: A review of the state of the art techniques

2020 ◽  
Vol 37 ◽  
pp. 100255 ◽  
Author(s):  
Saurabh Kulkarni ◽  
Sunil F. Rodd
Keyword(s):  
State Of The Art ◽  
Recommendation Systems ◽  
The State ◽  
Context Aware ◽  
Art Techniques

scholarly journals Coinductive Algorithms for Büchi Automata

2021 ◽  
Vol 180 (4) ◽  
pp. 351-373
Author(s):  
Denis Kuperberg ◽  
Laureline Pinault ◽  
Damien Pous
Keyword(s):  
State Space ◽  
State Of The Art ◽  
The State ◽  
Specific Structure ◽  
Büchi Automata ◽  
Deterministic Automata ◽  
Buchi Automata ◽  
Language Equivalence ◽  
Art Techniques

We propose a new algorithm for checking language equivalence of non-deterministic Büchi automata. We start from a construction proposed by Calbrix, Nivat and Podelski, which makes it possible to reduce the problem to that of checking equivalence of automata on finite words. Although this construction generates large and highly non-deterministic automata, we show how to exploit their specific structure and apply state-of-the art techniques based on coinduction to reduce the state-space that has to be explored. Doing so, we obtain algorithms which do not require full determinisation or complementation.

scholarly journals A Review and Comparison of the State-of-the-Art Techniques for Atrial Fibrillation Detection and Skin Hydration

2021 ◽  
Vol 2 ◽  
Author(s):  
Sidrah Liaqat ◽  
Kia Dashtipour ◽  
Adnan Zahid ◽  
Kamran Arshad ◽  
Sana Ullah Jan ◽  
...  
Keyword(s):  
Atrial Fibrillation ◽  
State Of The Art ◽  
The State ◽  
Skin Hydration ◽  
Hydration Level ◽  
Independent Review ◽  
Intelligent Models ◽  
Electrocardiogram Ecg ◽  
Fast Heart Rate ◽  
Art Techniques

Atrial fibrillation (AF) is one of the most common types of cardiac arrhythmia, with a prevalence of 1–2% in the community, increasing the risk of stroke and myocardial infarction. Early detection of AF, typically causing an irregular and abnormally fast heart rate, can help reduce the risk of strokes that are more common among older people. Intelligent models capable of automatic detection of AF in its earliest possible stages can improve the early diagnosis and treatment. Luckily, this can be made possible with the information about the heart's rhythm and electrical activity provided through electrocardiogram (ECG) and the decision-making machine learning-based autonomous models. In addition, AF has a direct impact on the skin hydration level and, hence, can be used as a measure for detection. In this paper, we present an independent review along with a comparative analysis of the state-of-the-art techniques proposed for AF detection using ECG and skin hydration levels. This paper also highlights the effects of AF on skin hydration level that is missing in most of the previous studies.

scholarly journals Lossless Image Compression Techniques: A State-of-the-Art Survey

Symmetry ◽  
2019 ◽  
Vol 11 (10) ◽  
pp. 1274 ◽  
Author(s):  
Md. Atiqur Rahman ◽  
Mohamed Hamada
Keyword(s):  
Image Compression ◽  
High Speed ◽  
Communication Theory ◽  
State Of The Art ◽  
Signal To Noise Ratio ◽  
Daily Basis ◽  
The State ◽  
Huge Amount ◽  
Lossless Image Compression ◽  
Art Techniques

Modern daily life activities result in a huge amount of data, which creates a big challenge for storing and communicating them. As an example, hospitals produce a huge amount of data on a daily basis, which makes a big challenge to store it in a limited storage or to communicate them through the restricted bandwidth over the Internet. Therefore, there is an increasing demand for more research in data compression and communication theory to deal with such challenges. Such research responds to the requirements of data transmission at high speed over networks. In this paper, we focus on deep analysis of the most common techniques in image compression. We present a detailed analysis of run-length, entropy and dictionary based lossless image compression algorithms with a common numeric example for a clear comparison. Following that, the state-of-the-art techniques are discussed based on some bench-marked images. Finally, we use standard metrics such as average code length (ACL), compression ratio (CR), pick signal-to-noise ratio (PSNR), efficiency, encoding time (ET) and decoding time (DT) in order to measure the performance of the state-of-the-art techniques.

Performance and trends in recent opinion retrieval techniques

2013 ◽  
Vol 30 (1) ◽  
pp. 76-105 ◽  
Author(s):  
Sylvester O. Orimaye ◽  
Saadat M. Alhashmi ◽  
Eu-Gene Siew
Keyword(s):  
State Of The Art ◽  
Performance Comparison ◽  
The State ◽  
Future Research ◽  
Research Directions ◽  
Opinion Retrieval ◽  
Future Research Directions ◽  
And Performance ◽  
Comparison Table ◽  
Art Techniques

AbstractThis paper presents trends and performance of opinion retrieval techniques proposed within the last 8 years. We identify major techniques in opinion retrieval and group them into four popular categories. We describe the state-of-the-art techniques for each category and emphasize on their performance and limitations. We then summarize with a performance comparison table for the techniques on different datasets. Finally, we highlight possible future research directions that can help solve existing challenges in opinion retrieval.

Considering Fine-Grained and Coarse-Grained Information for Context-Aware Recommendations

2020 ◽  
Author(s):  
Yiqin Luo ◽  
Yanpeng Sun ◽  
Liang Chang ◽  
Tianlong Gu ◽  
Chenzhong Bin ◽  
...  
Keyword(s):  
State Of The Art ◽  
Recommendation Systems ◽  
Coarse Grained ◽  
Evaluation Metrics ◽  
Parallel Structure ◽  
Context Aware ◽  
Preference Information ◽  
Fine Grained ◽  
Category Information ◽  
Candidate Item

Abstract In context-aware recommendation systems, most existing methods encode users’ preferences by mapping item and category information into the same space, which is just a stack of information. The item and category information contained in the interaction behaviours is not fully utilized. Moreover, since users’ preferences for a candidate item are influenced by the changes in temporal and historical behaviours, it is unreasonable to predict correlations between users and candidates by using users’ fixed features. A fine-grained and coarse-grained information based framework proposed in our paper which considers multi-granularity information of users’ historical behaviours. First, a parallel structure is provided to mine users’ preference information under different granularities. Then, self-attention and attention mechanisms are used to capture the dynamic preferences. Experiment results on two publicly available datasets show that our framework outperforms state-of-the-art methods across the calculated evaluation metrics.

scholarly journals A FRAMEWORK FOR COMMUNITY DETECTION IN HETEROGENEOUS MULTI-RELATIONAL NETWORKS

2014 ◽  
Vol 17 (06) ◽  
pp. 1450018 ◽  
Author(s):  
XIN LIU ◽  
WEICHU LIU ◽  
TSUYOSHI MURATA ◽  
KEN WAKITA
Keyword(s):  
Community Detection ◽  
Real World ◽  
State Of The Art ◽  
General Structure ◽  
The State ◽  
New Method ◽  
World Systems ◽  
Relational Networks ◽  
Relational Network ◽  
Art Techniques

There has been a surge of interest in community detection in homogeneous single-relational networks which contain only one type of nodes and edges. However, many real-world systems are naturally described as heterogeneous multi-relational networks which contain multiple types of nodes and edges. In this paper, we propose a new method for detecting communities in such networks. Our method is based on optimizing the composite modularity, which is a new modularity proposed for evaluating partitions of a heterogeneous multi-relational network into communities. Our method is parameter-free, scalable, and suitable for various networks with general structure. We demonstrate that it outperforms the state-of-the-art techniques in detecting pre-planted communities in synthetic networks. Applied to a real-world Digg network, it successfully detects meaningful communities.

scholarly journals Well-to-Seismic Tie of a Field Onshore of the Nigerian Delta

2021 ◽  
Vol 25 (1) ◽  
pp. 53-58
Author(s):  
S. Inichinbia ◽  
P.O. Saule
Keyword(s):  
Seismic Data ◽  
State Of The Art ◽  
The State ◽  
Spatial Extent ◽  
Strong Correlations ◽  
Rock Property ◽  
Well Location ◽  
Seismic Reflectors ◽  
Art Techniques

This work presents a modern procedure for understanding seismic data wavelets through well-toseismic tie on an onshore field in the Nigerian Delta using the state-of-the-art techniques. The purpose of this work is the correlation of formation tops and seismic  reflectors in the field. The objectives among others include the calibration of the seismic data in terms of polarity and phase, as well as to ensure that the seismic data is descriptive to well markers and discoveries, extending knowledge from the well location to rest of the field and reducing uncertainties. Logs from the two wells on the field and also logs from three wells on neighbouring fields were used to establish lateral continuity of the reservoirs H1000 and H4000. Their results show that the top, base and thickness of both reservoirs are quite variable laterally and this posed some challenges in the correlation from well to well. The field does not have checkshot data, so checkshot data from one of the wells on the neighbouring field was borrowed. Calibrated sonic and density logs of well01 and  well-02 were used to assess the seismic ties at the well locations. Strong correlations at the wells are fundamental to the evaluation of the spatial extent of the horizons around the wells from the seismic data. Seismic-to-well ties are a very important part of the interpreter’s business as they provide a means of correctly identifying horizons to pick, and estimating the wavelet for inverting seismic data to impedance and rock property indicators. Keywords: Seismic, horizons, correlation, synthetics

Long-acting microneedles: a progress report of the state-of-the-art techniques

2020 ◽  
Vol 25 (8) ◽  
pp. 1462-1468 ◽  
Author(s):  
Zhongjian Chen ◽  
Jingjing He ◽  
Jianping Qi ◽  
Quangang Zhu ◽  
Wei Wu ◽  
...  
Keyword(s):  
State Of The Art ◽  
Progress Report ◽  
The State ◽  
Long Acting ◽  
Art Techniques

DESIGN AND RESULTS OF THE 3RD ANNUAL SATISFIABILITY MODULO THEORIES COMPETITION (SMT-COMP 2007)

2008 ◽  
Vol 17 (04) ◽  
pp. 569-606 ◽  
Author(s):  
CLARK BARRETT ◽  
MORGAN DETERS ◽  
ALBERT OLIVERAS ◽  
AARON STUMP
Keyword(s):  
State Of The Art ◽  
The State ◽  
Satisfiability Modulo Theories ◽  
Art Techniques

The Satisfiability Modulo Theories Competition (SMT-COMP) is an annual competition aimed at stimulating the advance of the state-of-the-art techniques and tools developed by the Satisfiability Modulo Theories (SMT) community. As with the first two editions, SMT-COMP 2007 was held as a satellite event of CAV 2007, held July 3-7, 2007. This paper gives an overview of the rules, competition format, benchmarks, participants and results of SMT-COMP 2007.

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