Dialogue History Matters! Personalized Response Selection in Multi-Turn Retrieval-Based Chatbots

2021 ◽  
Vol 39 (4) ◽  
pp. 1-25
Author(s):  
Juntao Li ◽  
Chang Liu ◽  
Chongyang Tao ◽  
Zhangming Chan ◽  
Dongyan Zhao ◽  
...  
Keyword(s):  
Real World ◽  
Response Selection ◽  
Representation Learning ◽  
Large Datasets ◽  
Experimental Results ◽  
User Identification ◽  
Real Place ◽  
Real World Applications ◽  
Multi Level ◽  
The Given

Existing multi-turn context-response matching methods mainly concentrate on obtaining multi-level and multi-dimension representations and better interactions between context utterances and response. However, in real-place conversation scenarios, whether a response candidate is suitable not only counts on the given dialogue context but also other backgrounds, e.g., wording habits, user-specific dialogue history content. To fill the gap between these up-to-date methods and the real-world applications, we incorporate user-specific dialogue history into the response selection and propose a personalized hybrid matching network (PHMN). Our contributions are two-fold: (1) our model extracts personalized wording behaviors from user-specific dialogue history as extra matching information; (2) we perform hybrid representation learning on context-response utterances and explicitly incorporate a customized attention mechanism to extract vital information from context-response interactions so as to improve the accuracy of matching. We evaluate our model on two large datasets with user identification, i.e., personalized Ubuntu dialogue Corpus (P-Ubuntu) and personalized Weibo dataset (P-Weibo). Experimental results confirm that our method significantly outperforms several strong models by combining personalized attention, wording behaviors, and hybrid representation learning.

scholarly journals A New No Equilibrium Fractional Order Chaotic System, Dynamical Investigation, Synchronization, and Its Digital Implementation

Inventions ◽  
2021 ◽  
Vol 6 (3) ◽  
pp. 49
Author(s):  
Zain-Aldeen S. A. Rahman ◽  
Basil H. Jasim ◽  
Yasir I. A. Al-Yasir ◽  
Raed A. Abd-Alhameed ◽  
Bilal Naji Alhasnawi
Keyword(s):  
Adaptive Control ◽  
Fractional Order ◽  
Chaotic System ◽  
Real World ◽  
Experimental Results ◽  
Chaotic Attractors ◽  
State Variables ◽  
Digital Implementation ◽  
Dynamical Behaviors ◽  
Real World Applications

In this paper, a new fractional order chaotic system without equilibrium is proposed, analytically and numerically investigated, and numerically and experimentally tested. The analytical and numerical investigations were used to describe the system’s dynamical behaviors including the system equilibria, the chaotic attractors, the bifurcation diagrams, and the Lyapunov exponents. Based on the obtained dynamical behaviors, the system can excite hidden chaotic attractors since it has no equilibrium. Then, a synchronization mechanism based on the adaptive control theory was developed between two identical new systems (master and slave). The adaptive control laws are derived based on synchronization error dynamics of the state variables for the master and slave. Consequently, the update laws of the slave parameters are obtained, where the slave parameters are assumed to be uncertain and are estimated corresponding to the master parameters by the synchronization process. Furthermore, Arduino Due boards were used to implement the proposed system in order to demonstrate its practicality in real-world applications. The simulation experimental results were obtained by MATLAB and the Arduino Due boards, respectively, with a good consistency between the simulation results and the experimental results, indicating that the new fractional order chaotic system is capable of being employed in real-world applications.

Attenuation of Acoustic Emission Signals in Structural Interfaces

2012 ◽  
Vol 569 ◽  
pp. 343-346
Author(s):  
Xiang Hong Wang ◽  
Hong Wei Hu ◽  
Zhi Yong Zhang
Keyword(s):  
Acoustic Emission ◽  
Real World ◽  
Simple Structure ◽  
Size Structure ◽  
Experimental Results ◽  
Signal Energy ◽  
Real World Applications ◽  
Structural Interfaces ◽  
Ae Signals

Received acoustic emission (AE) signals are transmitted across structural interfaces in many real-world applications. This paper studies attenuation of the signals across two common structural interfaces. The experimental results indicate that interface has effects on attenuation, which depends on the relative scales of structures. Signal energy is strengthened due to multiple flections of signals on the small-size structure when an interface is constructed by different scales. Thus the received signals are distorted worse than the original signals. So it is a better way to mount sensors on a simple structure with a size as much as a structure incurred AE sources.

PROVIDING TIMELY UPDATED SEQUENTIAL PATTERNS IN DECISION MAKING

2010 ◽  
Vol 09 (06) ◽  
pp. 873-888 ◽  
Author(s):  
TZUNG-PEI HONG ◽  
CHING-YAO WANG ◽  
CHUN-WEI LIN
Keyword(s):  
Decision Making ◽  
Real Time ◽  
Real World ◽  
Experimental Results ◽  
Sequential Patterns ◽  
The Past ◽  
Large Databases ◽  
Real World Applications ◽  
Critical Task ◽  
Maintenance Process

Mining knowledge from large databases has become a critical task for organizations. Managers commonly use the obtained sequential patterns to make decisions. In the past, databases were usually assumed to be static. In real-world applications, however, transactions may be updated. In this paper, a maintenance algorithm for rapidly updating sequential patterns for real-time decision making is proposed. The proposed algorithm utilizes previously discovered large sequences in the maintenance process, thus greatly reducing the number of database rescans and improving performance. Experimental results verify the performance of the proposed approach. The proposed algorithm provides real-time knowledge that can be used for decision making.

scholarly journals Distributed and collaborative real-time vehicle detection and classification over the video streams

2017 ◽  
Vol 14 (4) ◽  
pp. 172988141772078 ◽  
Author(s):  
Seda Kul ◽  
Süleyman Eken ◽  
Ahmet Sayar
Keyword(s):  
Information Systems ◽  
Real Time ◽  
Real World ◽  
Traffic Management ◽  
Streaming Media ◽  
Vehicle Detection ◽  
Experimental Results ◽  
Traffic Surveillance ◽  
Video Streams ◽  
Real World Applications

Traffic surveillance cameras are widely used in traffic management and information systems. Processing streaming media in real time is resource and time-consuming processes and even impossible to realize in most real-world applications. To overcome the performance problems in such applications, this article introduces a middleware system based on pub/sub messaging protocol and a dispatcher to preprocess the streams in real time. Experimental results show that proposed middleware may be utilized in different areas such as infrastructure planning, traffic management, and prevention of traffic offenses.

Emotion Recognition from Speech Signals Using Elicited Data and Fuzzy KDA

2013 ◽  
Vol 385-386 ◽  
pp. 1385-1388
Author(s):  
Yong Qiang Bao ◽  
Li Zhao ◽  
Cheng Wei Hang
Keyword(s):  
Discriminant Analysis ◽  
Emotion Recognition ◽  
Real World ◽  
Recognition Rate ◽  
Experimental Results ◽  
Speech Emotion Recognition ◽  
Acoustic Features ◽  
Reliable System ◽  
Kernel Discriminant Analysis ◽  
Real World Applications

In this paper we introduced the application of Fuzzy KDA in speech emotion recognition using elicited data. The emotional data induced in a psychology experiment. The acted data is not suitable for developing real world applications and by using more naturalistic data we may build more reliable system. The emotional feature set is then constructed for modeling and recognition. A total of 372 low level acoustic features are used and kernel discriminant analysis is used for emotion recognition. The experimental results show a promising recognition rate.

scholarly journals Sequence Selection by Pareto Optimization

2018 ◽  
Author(s):  
Chao Qian ◽  
Chao Feng ◽  
Ke Tang
Keyword(s):  
Objective Function ◽  
Real World ◽  
Superior Performance ◽  
Sequence Length ◽  
Iterative Approach ◽  
Reasonable Time ◽  
Sequence Selection ◽  
Real World Applications ◽  
Approximation Guarantee ◽  
The Given

The problem of selecting a sequence of items from a universe that maximizes some given objective function arises in many real-world applications. In this paper, we propose an anytime randomized iterative approach POSeqSel, which maximizes the given objective function and minimizes the sequence length simultaneously. We prove that for any previously studied objective function, POSeqSel using a reasonable time can always reach or improve the best known approximation guarantee. Empirical results exhibit the superior performance of POSeqSel.

scholarly journals An Introduction to Swarm Robotics

ISRN Robotics ◽  
2013 ◽  
Vol 2013 ◽  
pp. 1-10 ◽  
Author(s):  
Iñaki Navarro ◽  
Fernando Matía
Keyword(s):  
Social Insects ◽  
Real World ◽  
Swarm Robotics ◽  
Experimental Results ◽  
Robotic Systems ◽  
Complex Tasks ◽  
Real World Applications ◽  
The Future

Swarm robotics is a field of multi-robotics in which large number of robots are coordinated in a distributed and decentralised way. It is based on the use of local rules, and simple robots compared to the complexity of the task to achieve, and inspired by social insects. Large number of simple robots can perform complex tasks in a more efficient way than a single robot, giving robustness and flexibility to the group. In this article, an overview of swarm robotics is given, describing its main properties and characteristics and comparing it to general multi-robotic systems. A review of different research works and experimental results, together with a discussion of the future swarm robotics in real world applications completes this work.

Semi-Supervised Outlier Detection with Only Positive and Unlabeled Data Based on Fuzzy Clustering

2015 ◽  
Vol 24 (03) ◽  
pp. 1550003 ◽  
Author(s):  
Armin Daneshpazhouh ◽  
Ashkan Sami
Keyword(s):  
Intrusion Detection ◽  
Outlier Detection ◽  
Fuzzy Clustering ◽  
Real World ◽  
State Of The Art ◽  
Real Data ◽  
Experimental Results ◽  
The Other ◽  
Data Sets ◽  
Real World Applications

The task of semi-supervised outlier detection is to find the instances that are exceptional from other data, using some labeled examples. In many applications such as fraud detection and intrusion detection, this issue becomes more important. Most existing techniques are unsupervised. On the other hand, semi-supervised approaches use both negative and positive instances to detect outliers. However, in many real world applications, very few positive labeled examples are available. This paper proposes an innovative approach to address this problem. The proposed method works as follows. First, some reliable negative instances are extracted by a kNN-based algorithm. Afterwards, fuzzy clustering using both negative and positive examples is utilized to detect outliers. Experimental results on real data sets demonstrate that the proposed approach outperforms the previous unsupervised state-of-the-art methods in detecting outliers.

scholarly journals Restart and Random Walk in Local Search for Maximum Vertex Weight Cliques with Evaluations in Clustering Aggregation

2017 ◽  
Author(s):  
Yi Fan ◽  
Nan Li ◽  
Chengqian Li ◽  
Zongjie Ma ◽  
Longin Jan Latecki ◽  
...  
Keyword(s):  
Random Walk ◽  
Local Search ◽  
Real World ◽  
State Of The Art ◽  
Real Data ◽  
Experimental Results ◽  
Data Sets ◽  
Vertex Weight ◽  
Real World Applications ◽  
Clustering Aggregation

The Maximum Vertex Weight Clique (MVWC) problem is NP-hard and also important in real-world applications. In this paper we propose to use the restart and the random walk strategies to improve local search for MVWC. If a solution is revisited in some particular situation, the search will restart. In addition, when the local search has no other options except dropping vertices, it will use random walk. Experimental results show that our solver outperforms state-of-the-art solvers in DIMACS and finds a new best-known solution. Also it is the unique solver which is comparable with state-of-the-art methods on both BHOSLIB and large crafted graphs. Furthermore we evaluated our solver in clustering aggregation. Experimental results on a number of real data sets demonstrate that our solver outperforms the state-of-the-art for solving the derived MVWC problem and helps improve the final clustering results.

scholarly journals Bursting the Filter Bubble: Fairness-Aware Network Link Prediction

2020 ◽  
Vol 34 (01) ◽  
pp. 841-848
Author(s):  
Farzan Masrour ◽  
Tyler Wilson ◽  
Heng Yan ◽  
Pang-Ning Tan ◽  
Abdol Esfahanian
Keyword(s):  
Social Networking ◽  
Real World ◽  
Link Prediction ◽  
Representation Learning ◽  
Experimental Results ◽  
Adversarial Network ◽  
Network Link ◽  
Network Modularity ◽  
Filter Bubble ◽  
Real World Datasets

Link prediction is an important task in online social networking as it can be used to infer new or previously unknown relationships of a network. However, due to the homophily principle, current algorithms are susceptible to promoting links that may lead to increase segregation of the network—an effect known as filter bubble. In this study, we examine the filter bubble problem from the perspective of algorithm fairness and introduce a dyadic-level fairness criterion based on network modularity measure. We show how the criterion can be utilized as a postprocessing step to generate more heterogeneous links in order to overcome the filter bubble problem. In addition, we also present a novel framework that combines adversarial network representation learning with supervised link prediction to alleviate the filter bubble problem. Experimental results conducted on several real-world datasets showed the effectiveness of the proposed methods compared to other baseline approaches, which include conventional link prediction and fairness-aware methods for i.i.d data.

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