Statistics-Based Outlier Detection and Correction Method for Amazon Customer Reviews

People nowadays use the internet to project their assessments, impressions, ideas, and observations about various subjects or products on numerous social networking sites. These sites serve as a great source to gather data for data analytics, sentiment analysis, natural language processing, etc. Conventionally, the true sentiment of a customer review matches its corresponding star rating. There are exceptions when the star rating of a review is opposite to its true nature. These are labeled as the outliers in a dataset in this work. The state-of-the-art methods for anomaly detection involve manual searching, predefined rules, or traditional machine learning techniques to detect such instances. This paper conducts a sentiment analysis and outlier detection case study for Amazon customer reviews, and it proposes a statistics-based outlier detection and correction method (SODCM), which helps identify such reviews and rectify their star ratings to enhance the performance of a sentiment analysis algorithm without any data loss. This paper focuses on performing SODCM in datasets containing customer reviews of various products, which are (a) scraped from Amazon.com and (b) publicly available. The paper also studies the dataset and concludes the effect of SODCM on the performance of a sentiment analysis algorithm. The results exhibit that SODCM achieves higher accuracy and recall percentage than other state-of-the-art anomaly detection algorithms.     

Detecting community structure using label propagation with weighted coherent neighborhood propinquity

Community detection has become an important methodology to understand the organization and function of various real-world networks. The label propagation algorithm (LPA) is an almost linear time algorithm proved to be effective in finding a good community structure. However, LPA has a limitation caused by its one-hop horizon. Specifically, each node in LPA adopts the label shared by most of its one-hop neighbors; much network topology information is lost in this process, which we believe is one of the main reasons for its instability and poor performance. Therefore in this paper we introduce a measure named weighted coherent neighborhood propinquity (weighted-CNP) to represent the probability that a pair of vertices are involved in the same community. In label update, a node adopts the label that has the maximum weighted-CNP instead of the one that is shared by most of its neighbors. We propose a dynamic and adaptive weighted-CNP called entropic-CNP by using the principal of entropy to modulate the weights. Furthermore, we propose a framework to integrate the weighted-CNP in other algorithms in detecting community structure. We test our algorithm on both computer-generated networks and real-world networks. The experimental results show that our algorithm is more robust and effective than LPA in large-scale networks.     

Ant colony clustering with fitness perception and pheromone diffusion for community detection in complex networks

Community structure detection in complex networks has been intensively investigated in recent years. In this paper, we propose an adaptive approach based on ant colony clustering to discover communities in a complex network. The focus of the method is the clustering process of an ant colony in a virtual grid, where each ant represents a node in the complex network. During the ant colony search, the method uses a new fitness function to percept local environment and employs a pheromone diffusion model as a global information feedback mechanism to realize information exchange among ants. A significant advantage of our method is that the locations in the grid environment and the connections of the complex network structure are simultaneously taken into account in ants moving. Experimental results on computer-generated and real-world networks show the capability of our method to successfully detect community structures.     

Community detection in complex networks by density-based clustering

We proposed a method to find the community structure in a complex network by density-based clustering. Physical topological distance is introduced in density-based clustering for determining a distance function of specific influence functions. According to the distribution of the data, the community structures are uncovered. The method keeps a better connection mode of the community structure than the existing algorithms in terms of modularity, which can be viewed as a basic characteristic of community detection in the future. Moreover, experimental results indicate that the proposed method is efficient and effective to be used for community detection of medium and large networks.     

High pressure 17O NMR study of solvent exchange on square planar complexes: Water exchange on [Pd(dien)H2O]2+

Abstract

The water exchange reaction of [Pd(dien)H₂O]²⁺ (dien = diethylenetriamine) was studied as function of temperature (268-308 K) and pressure 0.1-197 MPa) using ₁₇O NMR techniques. The rate and activation parameters are: k_cx = 5100 s^?1 at 298 K; ΔH^# =38 kJ mol^?1; ΔS^# = -47 JK^?1 mol^?1; ΔV^# = -2.8 cm³ mol^?1 at 296 K. The results are discussed in reference to solvent exchange data for other Pt(II) and Pd(II) complexes, and are interpreted in terms of an associatively activated substitution process.     

Mehr-Detektor-Anordnung für die Koinzidenzmessung von Positronenstrahlern

Procedures are given for the title compounds, which allow their preparation in high chemical purity and without any depletion of the ¹⁵N-content. A nitrogen isotope exchange between NOBF₄ and ¹⁵N₂O₃ was found, but it is too slow for preparative purposes.     

Zur Berechnung von Geometriefaktoren bei der Kernstrahlungsmessung

Der Geometriefaktor von radioaktiven umschlossenen oder offenen Strahlenquellen hängt bei der Messung mittels einer Kernstrahlungsmeßsonde von der räumlichen Anordnung der Strahlenquelle zu der strahlenexponierten wirksamen Fläche des Detektors und von der Geometrie der Strahlenquelle selbst ab. Fūr punktförmige Strahler in verschiedenen Positionen, Geraden, Kreisflächen und Zylinder wurde in möglichst einheitlicher Vorgehensweise die Berechnung der Geometriefaktoren bezüglich kreisförmiger ebener Detektionsflächen vorgenommen und rechentechnisch in Form von BESM 6-Algolprogrammen realisiert. Die Berechnungsergebnisse sind untereinander konsistent und wurden möglichst durch unabhängige Verfahren oder experimentelle Werte kontrolliert. Die Rechengenauigkeit kann gemäß den vorliegenden Anforderungen frei gewählt werden.     

The effect of thermal reactor neutron irradiation on semi-insulating GaN

Semi-insulating Gallium nitride was irradiated by fast and thermal neutrons with fluences from 10¹⁴ to 10¹⁶ n/cm². Depth-resolved cathodoluminescence spectroscopy was used to determine defects changes before and after irradiation. The results revealed two kinds of defects affected near-band emission recombination from two opposite directions. One was attributed to irradiation-induced N vacancies that contribute to near-band emission recombination. Another was attributed to irradiation-induced deep level defects that contribute to sub-band gap recombination and thus decrease the near-band emission recombination.     

Growth of tertiary dendritic arms during the transient directional solidification of hypoeutectic Pb–Sb alloys

Despite the importance of a complete characterization of dendritic patterns in castings, the availability of studies on the development of tertiary dendrite arms is scarce in the literature. In the present study, the tip cooling rate, local solidification time, primary and tertiary dendrite arm spacings have been determined in Pb–Sb alloys castings directionally solidified under unsteady-state heat flow conditions. The alloys compositions experimentally examined are widely used in the as-cast condition for the manufacture of positive and negative grids of lead-acid batteries. The initial growth of tertiary dendritic arms from the secondary branches was found to occur only for a Pb–3.5 wt% Sb alloy at cooling rates in the range 0.4–0.2?K/s, with no evidence of this spacing pattern for Pb–Sb alloys having lower solute content. Tertiary dendritic branches have been observed along the entire casting lengths for alloys of the Pb–Sb hypoeutectic range having compositions higher than 4.0 wt% Sb. It is shown that a power function experimental law with a characteristic ?0.55 exponent is able to characterize the tertiary spacing evolution with the solidification cooling rate for alloys compositions ≥4.0 wt% Sb. The only exception was the Pb–3.5 wt% Sb alloy for which λ ₃ exhibited significant lower values when compared with the experimental values obtained for the other Pb–Sb alloys for a same solidification cooling rate.     

Spectral Database Systems: A Review

Abstract: Spectroscopy has been demonstrated to be an important method of analysis and detection. A spectral database system (SDBS) can not only satisfy the traditional requirements for spectral management but also provides several new functions, including spectra sharing on the website and web-based and real-time analysis and detection. Chemists and spectroscopists could analyze and detect pure materials and some mixtures rapidly with the help of standard SDBS, and now they are trying to improve these systems to fulfill rapid analysis for complex mixtures, even those as complex as agro-products. Overall, SDBS make it possible to analyze and detect unknown samples rapidly and nondestructively. This article focuses on significant progress in research on infrared (IR), near-infrared (NIR), and Raman SDBSs. Additionally, the drawbacks and obstacles of SDBSs are summarized and trends are discussed.