scholarly journals Extractive Multi-Document Summarization Model Based On Different Integrations of Double Similarity Measures

2020 ◽  
pp. 1498-1511
Author(s):  
Dheyaa Abdulameer Mohammed ◽  
Nasreen J. Kadhim
Keyword(s):  
Information Overload ◽  
Positive Impact ◽  
Similarity Measures ◽  
Text Summarization ◽  
Text Similarity ◽  
Document Summarization ◽  
Model Based ◽  
Proposed Model ◽  
Content Coverage ◽  
Summarization System

Currently, the prominence of automatic multi document summarization task belongs to the information rapid increasing on the Internet. Automatic document summarization technology is progressing and may offer a solution to the problem of information overload.  Automatic text summarization system has the challenge of producing a high quality summary. In this study, the design of generic text summarization model based on sentence extraction has been redirected into a more semantic measure reflecting individually the two significant objectives: content coverage and diversity when generating summaries from multiple documents as an explicit optimization model. The proposed two models have been then coupled and defined as a single-objective optimization problem. Also, for improving the performance of the proposed model, different integrations concerning two similarity measures have been introduced and applied to the proposed model along with the single similarity measures that are based on using Cosine, Dice and  similarity measures for measuring text similarity. For solving the proposed model, Genetic Algorithm (GA) has been used. Document sets supplied by Document Understanding Conference 2002 ( ) have been used for the proposed system as an evaluation dataset. Also, as an evaluation metric, Recall-Oriented Understudy for Gisting Evaluation ( ) toolkit has been used for performance evaluation of the proposed method. Experimental results have illustrated the positive impact of measuring text similarity using double integration of similarity measures against single similarity measure when applied to the proposed model wherein the best performance in terms of  and  has been recorded for the integration of Cosine similarity and  similarity.

scholarly journals Exploiting Semantic Term Relations in Text Summarization

2022 ◽  
Vol 12 (1) ◽  
pp. 0-0
Keyword(s):  
Similarity Measure ◽  
Text Summarization ◽  
Experimental Results ◽  
Semantic Relations ◽  
Document Summarization ◽  
Term Frequency ◽  
Redundancy Removal ◽  
Term Similarity ◽  
Summarization System

The traditional frequency based approach to creating multi-document extractive summary ranks sentences based on scores computed by summing up TF*IDF weights of words contained in the sentences. In this approach, TF or term frequency is calculated based on how frequently a term (word) occurs in the input and TF calculated in this way does not take into account the semantic relations among terms. In this paper, we propose methods that exploits semantic term relations for improving sentence ranking and redundancy removal steps of a summarization system. Our proposed summarization system has been tested on DUC 2003 and DUC 2004 benchmark multi-document summarization datasets. The experimental results reveal that performance of our multi-document text summarizer is significantly improved when the distributional term similarity measure is used for finding semantic term relations. Our multi-document text summarizer also outperforms some well known summarization baselines to which it is compared.

scholarly journals A Multi-document Summarization System for News Articles in Portuguese using Integer Linear Programming

2019 ◽  
Author(s):  
Laerth Gomes ◽  
Hilário Oliveira
Keyword(s):  
Linear Programming ◽  
Integer Linear Programming ◽  
Relevant Information ◽  
Brazilian Portuguese ◽  
Text Summarization ◽  
Document Summarization ◽  
Automatic Text Summarization ◽  
Summarization System ◽  
Automatic Text ◽  
Intense Research

Automatic Text Summarization (ATS) has been demanding intense research in recent years. Its importance is given the fact that ATS systems can aid in the processing of large amounts of textual documents. The ATS task aims to create a summary of one or more documents by extracting their most relevant information. Despite the existence of several works, researches involving the development of ATS systems for documents written in Brazilian Portuguese are still a few. In this paper, we propose a multi-document summarization system following a concept-based approach using Integer Linear Programming for the generation of summaries from news articles written in Portuguese. Experiments using the CSTNews corpus were performed to evaluate different aspects of the proposed system. The experimental results obtained regarding the ROUGE measures demonstrate that the developed system presents encourage results, outperforming other works of the literature.

scholarly journals Similitude Based Segment Graph Construction and Segment Ranking for Automatic Summarization of Text Document

2022 ◽  
Vol 19 (1) ◽  
pp. 1719
Author(s):  
Saravanan Arumugam ◽  
Sathya Bama Subramani
Keyword(s):  
Information Gain ◽  
Text Summarization ◽  
Text Documents ◽  
Document Summarization ◽  
Gain Ratio ◽  
Average Rank ◽  
Text Document ◽  
Proposed Model ◽  
Feature Values ◽  
Information Gain Ratio

With the increase in the amount of data and documents on the web, text summarization has become one of the significant fields which cannot be avoided in today’s digital era. Automatic text summarization provides a quick summary to the user based on the information presented in the text documents. This paper presents the automated single document summarization by constructing similitude graphs from the extracted text segments. On extracting the text segments, the feature values are computed for all the segments by comparing them with the title and the entire document and by computing segment significance using the information gain ratio. Based on the computed features, the similarity between the segments is evaluated to construct the graph in which the vertices are the segments and the edges specify the similarity between them. The segments are ranked for including them in the extractive summary by computing the graph score and the sentence segment score. The experimental analysis has been performed using ROUGE metrics and the results are analyzed for the proposed model. The proposed model has been compared with the various existing models using 4 different datasets in which the proposed model acquired top 2 positions with the average rank computed on various metrics such as precision, recall, F-score. HIGHLIGHTS Paper presents the automated single document summarization by constructing similitude graphs from the extracted text segments It utilizes information gain ratio, graph construction, graph score and the sentence segment score computation Results analysis has been performed using ROUGE metrics with 4 popular datasets in the document summarization domain The model acquired top 2 positions with the average rank computed on various metrics such as precision, recall, F-score GRAPHICAL ABSTRACT

A Modified Dugoff Tire Model for Combined-slip Forces

2010 ◽  
Vol 38 (3) ◽  
pp. 228-244 ◽  
Author(s):  
Nenggen Ding ◽  
Saied Taheri
Keyword(s):  
Vehicle Dynamics ◽  
Tire Model ◽  
Magic Formula ◽  
Model Based ◽  
Proposed Model ◽  
Road Friction ◽  
On Line ◽  
Double Lane Change ◽  
Tire Forces ◽  
Tire Models

Abstract Easy-to-use tire models for vehicle dynamics have been persistently studied for such applications as control design and model-based on-line estimation. This paper proposes a modified combined-slip tire model based on Dugoff tire. The proposed model takes emphasis on less time consumption for calculation and uses a minimum set of parameters to express tire forces. Modification of Dugoff tire model is made on two aspects: one is taking different tire/road friction coefficients for different magnitudes of slip and the other is employing the concept of friction ellipse. The proposed model is evaluated by comparison with the LuGre tire model. Although there are some discrepancies between the two models, the proposed combined-slip model is generally acceptable due to its simplicity and easiness to use. Extracting parameters from the coefficients of a Magic Formula tire model based on measured tire data, the proposed model is further evaluated by conducting a double lane change maneuver, and simulation results show that the trajectory using the proposed tire model is closer to that using the Magic Formula tire model than Dugoff tire model.

An Automatic Text Summarization Method with the Concern of Covering Complete Formation

2020 ◽  
Vol 13 (5) ◽  
pp. 977-986
Author(s):  
Srinivasa Rao Kongara ◽  
Dasika Sree Rama Chandra Murthy ◽  
Gangadhara Rao Kancherla
Keyword(s):  
Research Method ◽  
Research Work ◽  
Fuzzy Rule ◽  
Text Summarization ◽  
Document Summarization ◽  
Summarization Method ◽  
Overall Evaluation ◽  
Multiple Documents ◽  
Rule System ◽  
Value Decomposition

Background: Text summarization is the process of generating a short description of the entire document which is more difficult to read. This method provides a convenient way of extracting the most useful information and a short summary of the documents. In the existing research work, this is focused by introducing the Fuzzy Rule-based Automated Summarization Method (FRASM). Existing work tends to have various limitations which might limit its applicability to the various real-world applications. The existing method is only suitable for the single document summarization where various applications such as research industries tend to summarize information from multiple documents. Methods: This paper proposed Multi-document Automated Summarization Method (MDASM) to introduce the summarization framework which would result in the accurate summarized outcome from the multiple documents. In this work, multi-document summarization is performed whereas in the existing system only single document summarization was performed. Initially document clustering is performed using modified k means cluster algorithm to group the similar kind of documents that provides the same meaning. This is identified by measuring the frequent term measurement. After clustering, pre-processing is performed by introducing the Hybrid TF-IDF and Singular value decomposition technique which would eliminate the irrelevant content and would result in the required content. Then sentence measurement is one by introducing the additional metrics namely Title measurement in addition to the existing work metrics to accurately retrieve the sentences with more similarity. Finally, a fuzzy rule system is applied to perform text summarization. Results: The overall evaluation of the research work is conducted in the MatLab simulation environment from which it is proved that the proposed research method ensures the optimal outcome than the existing research method in terms of accurate summarization. MDASM produces 89.28% increased accuracy, 89.28% increased precision, 89.36% increased recall value and 70% increased the f-measure value which performs better than FRASM. Conclusion: The summarization processes carried out in this work provides the accurate summarized outcome.

A new path loss model based on the volumetric occupancy rate for the pine forests at 5G frequency band

2020 ◽  
pp. 1-10
Author(s):  
Abdullah Genc
Keyword(s):  
Path Loss ◽  
Forest Area ◽  
Occupancy Rate ◽  
Loss Model ◽  
Path Loss Model ◽  
Model Based ◽  
Proposed Model ◽  
Pine Trees ◽  
Foliage Density ◽  
Reference Measurements

Abstract In this paper, a new empirical path loss model based on frequency, distance, and volumetric occupancy rate is generated at the 3.5 and 4.2 GHz in the scope of 5G frequency bands. This study aims to determine the effect of the volumetric occupancy rate on path loss depending on the foliage density of the trees in the pine forest area. Using 4.2 GHz and the effect of the volumetric occupancy rate contributes to the literature in terms of novelty. Both the reference measurements to generate a model and verification measurements to verify the proposed models are conducted in three different regions of the forest area with double ridged horn antennas. These regions of the artificial forest area consist of regularly sorted and identical pine trees. Root mean square error (RMSE) and R-squared values are calculated to evaluate the performance of the proposed model. For 3.5 and 4.2 GHz, while the RMSEs are 3.983 and 3.883, the values of R-squared are 0.967 and 0.963, respectively. Additionally, the results are compared with four path loss models which are commonly used in the forest area. The proposed one has the best performance among the other models with values 3.98 and 3.88 dB for 3.5 and 4.2 GHz.

scholarly journals Lane Departure Warning Estimation Using Yaw Acceleration

2020 ◽  
Vol 11 (1) ◽  
pp. 102-111
Author(s):  
Em Poh Ping ◽  
J. Hossen ◽  
Wong Eng Kiong
Keyword(s):  
Vehicle Dynamics ◽  
Dynamic Responses ◽  
Dynamics Simulation ◽  
Steering Wheel ◽  
Mathematical Representation ◽  
Vehicle Speed ◽  
Lane Departure Warning ◽  
Model Based ◽  
Lane Departure ◽  
Proposed Model

AbstractLane departure collisions have contributed to the traffic accidents that cause millions of injuries and tens of thousands of casualties per year worldwide. Due to vision-based lane departure warning limitation from environmental conditions that affecting system performance, a model-based vehicle dynamics framework is proposed for estimating the lane departure event by using vehicle dynamics responses. The model-based vehicle dynamics framework mainly consists of a mathematical representation of 9-degree of freedom system, which permitted to pitch, roll, and yaw as well as to move in lateral and longitudinal directions with each tire allowed to rotate on its axle axis. The proposed model-based vehicle dynamics framework is created with a ride model, Calspan tire model, handling model, slip angle, and longitudinal slip subsystems. The vehicle speed and steering wheel angle datasets are used as the input in vehicle dynamics simulation for predicting lane departure event. Among the simulated vehicle dynamic responses, the yaw acceleration response is observed to provide earlier insight in predicting the future lane departure event compared to other vehicle dynamics responses. The proposed model-based vehicle dynamics framework had shown the effectiveness in estimating lane departure using steering wheel angle and vehicle speed inputs.

scholarly journals A Reference Framework to Combine Model-Based Design and AR to Improve Social Sustainability

2021 ◽  
Vol 13 (4) ◽  
pp. 2031
Author(s):  
Fabio Grandi ◽  
Riccardo Karim Khamaisi ◽  
Margherita Peruzzini ◽  
Roberto Raffaeli ◽  
Marcello Pellicciari
Keyword(s):  
Positive Impact ◽  
Cost Effective ◽  
Digital Models ◽  
Model Based ◽  
Digital Contents ◽  
Recent Developments ◽  
Virtual Simulations ◽  
Product And Process ◽  
The Impact ◽  
Time Information

Product and process digitalization is pervading numerous areas in the industry to improve quality and reduce costs. In particular, digital models enable virtual simulations to predict product and process performances, as well as to generate digital contents to improve the general workflow. Digital models can also contain additional contents (e.g., model-based design (MBD)) to provide online and on-time information about process operations and management, as well as to support operator activities. The recent developments in augmented reality (AR) offer new specific interfaces to promote the great diffusion of digital contents into industrial processes, thanks to flexible and robust applications, as well as cost-effective devices. However, the impact of AR applications on sustainability is still poorly explored in research. In this direction, this paper proposed an innovative approach to exploit MBD and introduce AR interfaces in the industry to support human intensive processes. Indeed, in those processes, the human contribution is still crucial to guaranteeing the expected product quality (e.g., quality inspection). The paper also analyzed how this new concept can benefit sustainability and define a set of metrics to assess the positive impact on sustainability, focusing on social aspects.

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