E-Commerce - Automatic Building of Collection of ProductsJeena Thampi
This paper has explained how to automate the building of E-commerce intent-based product collection using a pre-trained model. They have covered the sampling method, training, and evaluation method. They were also able to achieve increased CTR (click-through rate), CVR (conversion rate), and order diversity when compared to manually created product collections.
Suggestion Generation for Specific Erroneous Part in a Sentence using Deep Le...ijtsrd
Natural Language Processing NLP is the one of the major filed of Natural Language Generation NLG . NLG can generate natural language from a machine representation. Generating suggestions for a sentence especially for Indian languages is much difficult. One of the major reason is that it is morphologically rich and the format is just reverse of English language. By using deep learning approach with the help of Long Short Term Memory LSTM layers we can generate a possible set of solutions for erroneous part in a sentence. To effectively generate a bunch of sentences having equivalent meaning as the original sentence using Deep Learning DL approach is to train a model on this task, e.g. we need thousands of examples of inputs and outputs with which to train a model. Veena S Nair | Amina Beevi A ""Suggestion Generation for Specific Erroneous Part in a Sentence using Deep Learning"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23842.pdf
Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/23842/suggestion-generation-for-specific-erroneous-part-in-a-sentence-using-deep-learning/veena-s-nair
Parameters Optimization for Improving ASR Performance in Adverse Real World N...Waqas Tariq
From the existing research it has been observed that many techniques and methodologies are available for performing every step of Automatic Speech Recognition (ASR) system, but the performance (Minimization of Word Error Recognition-WER and Maximization of Word Accuracy Rate- WAR) of the methodology is not dependent on the only technique applied in that method. The research work indicates that, performance mainly depends on the category of the noise, the level of the noise and the variable size of the window, frame, frame overlap etc is considered in the existing methods. The main aim of the work presented in this paper is to use variable size of parameters like window size, frame size and frame overlap percentage to observe the performance of algorithms for various categories of noise with different levels and also train the system for all size of parameters and category of real world noisy environment to improve the performance of the speech recognition system. This paper presents the results of Signal-to-Noise Ratio (SNR) and Accuracy test by applying variable size of parameters. It is observed that, it is really very hard to evaluate test results and decide parameter size for ASR performance improvement for its resultant optimization. Hence, this study further suggests the feasible and optimum parameter size using Fuzzy Inference System (FIS) for enhancing resultant accuracy in adverse real world noisy environmental conditions. This work will be helpful to give discriminative training of ubiquitous ASR system for better Human Computer Interaction (HCI). Keywords: ASR Performance, ASR Parameters Optimization, Multi-Environmental Training, Fuzzy Inference System for ASR, ubiquitous ASR system, Human Computer Interaction (HCI)
An Improved Approach for Word Ambiguity RemovalWaqas Tariq
Word ambiguity removal is a task of removing ambiguity from a word, i.e. correct sense of word is identified from ambiguous sentences. This paper describes a model that uses Part of Speech tagger and three categories for word sense disambiguation (WSD). Human Computer Interaction is very needful to improve interactions between users and computers. For this, the Supervised and Unsupervised methods are combined. The WSD algorithm is used to find the efficient and accurate sense of a word based on domain information. The accuracy of this work is evaluated with the aim of finding best suitable domain of word. Keywords: Human Computer Interaction, Supervised Training, Unsupervised Learning, Word Ambiguity, Word sense disambiguation
E-Commerce - Automatic Building of Collection of ProductsJeena Thampi
This paper has explained how to automate the building of E-commerce intent-based product collection using a pre-trained model. They have covered the sampling method, training, and evaluation method. They were also able to achieve increased CTR (click-through rate), CVR (conversion rate), and order diversity when compared to manually created product collections.
Suggestion Generation for Specific Erroneous Part in a Sentence using Deep Le...ijtsrd
Natural Language Processing NLP is the one of the major filed of Natural Language Generation NLG . NLG can generate natural language from a machine representation. Generating suggestions for a sentence especially for Indian languages is much difficult. One of the major reason is that it is morphologically rich and the format is just reverse of English language. By using deep learning approach with the help of Long Short Term Memory LSTM layers we can generate a possible set of solutions for erroneous part in a sentence. To effectively generate a bunch of sentences having equivalent meaning as the original sentence using Deep Learning DL approach is to train a model on this task, e.g. we need thousands of examples of inputs and outputs with which to train a model. Veena S Nair | Amina Beevi A ""Suggestion Generation for Specific Erroneous Part in a Sentence using Deep Learning"" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-4 , June 2019, URL: https://www.ijtsrd.com/papers/ijtsrd23842.pdf
Paper URL: https://www.ijtsrd.com/engineering/computer-engineering/23842/suggestion-generation-for-specific-erroneous-part-in-a-sentence-using-deep-learning/veena-s-nair
Parameters Optimization for Improving ASR Performance in Adverse Real World N...Waqas Tariq
From the existing research it has been observed that many techniques and methodologies are available for performing every step of Automatic Speech Recognition (ASR) system, but the performance (Minimization of Word Error Recognition-WER and Maximization of Word Accuracy Rate- WAR) of the methodology is not dependent on the only technique applied in that method. The research work indicates that, performance mainly depends on the category of the noise, the level of the noise and the variable size of the window, frame, frame overlap etc is considered in the existing methods. The main aim of the work presented in this paper is to use variable size of parameters like window size, frame size and frame overlap percentage to observe the performance of algorithms for various categories of noise with different levels and also train the system for all size of parameters and category of real world noisy environment to improve the performance of the speech recognition system. This paper presents the results of Signal-to-Noise Ratio (SNR) and Accuracy test by applying variable size of parameters. It is observed that, it is really very hard to evaluate test results and decide parameter size for ASR performance improvement for its resultant optimization. Hence, this study further suggests the feasible and optimum parameter size using Fuzzy Inference System (FIS) for enhancing resultant accuracy in adverse real world noisy environmental conditions. This work will be helpful to give discriminative training of ubiquitous ASR system for better Human Computer Interaction (HCI). Keywords: ASR Performance, ASR Parameters Optimization, Multi-Environmental Training, Fuzzy Inference System for ASR, ubiquitous ASR system, Human Computer Interaction (HCI)
An Improved Approach for Word Ambiguity RemovalWaqas Tariq
Word ambiguity removal is a task of removing ambiguity from a word, i.e. correct sense of word is identified from ambiguous sentences. This paper describes a model that uses Part of Speech tagger and three categories for word sense disambiguation (WSD). Human Computer Interaction is very needful to improve interactions between users and computers. For this, the Supervised and Unsupervised methods are combined. The WSD algorithm is used to find the efficient and accurate sense of a word based on domain information. The accuracy of this work is evaluated with the aim of finding best suitable domain of word. Keywords: Human Computer Interaction, Supervised Training, Unsupervised Learning, Word Ambiguity, Word sense disambiguation
1. RESUME
Dhulipalla Rajitha
Mobile: +91-9032848654
E-mail : rajita.dhulipalla@gmail.com
Career Objective:
A Position in Software Industry seeking challenging avenues where my technical
experience, educational Potential and teamwork match the growth and strength of the
organization and to contribute to Organizational goals with betterment of my career prospects
and equipping myself with rich technical skills.
Educational Qualification:
Technical skills:
Operating system Windows7,WindowsXP
Core Skills Mat lab, E-cad
Languages C language, Core java, JDBC,Servlets,SQL
Achievements:
Presented a project on “SOLAR DRIVEN VEHICLE WITH DRUNKENPEOPLE AND SEAT
BELT IDENTIFICATION” in Narasaraopet Institute of Technology.
Presented a PPT (Paper Presentation) On “4G Technology” in Narasaraopet Institute Of
Technology.
Presented a PPT (Paper Presentation) On “Palm Wein Technology” in Krishnaveni Engineering
College For Women.
In B.tech I got medal for studies.
Qualification Duration School/College University Percentage
B.Tech
(E.C.E.) 2010-2014
Narasaraopeta Inistitute Of
Technology, Narasaraopet
J.N.T.U.-K 79%
Intermediate 2008-2010
Sri Chaitanya Junior
College, Guntur
Board Of
Intermediate
Education
90%
SSC
2007-2008
Viswa Bharathi High
School, Addanki
Board Of
Secondary
Education
83%
2. Project Details:
Title : A High Throughput and size efficient NOC buffer design method.
Team Size :4
Role :Team leader
DESCRPTION:
This paper presents a high-throughput and size efficient buffer design method for an
application specific NoC. The method firstly configures on chip buffer according with the
mapping position of IP and the routing path of communication pairs, then computes the
minimum value of buffer's size under NoC performance guarantee. Under the same
buffer size, the experiments show that the method results in the 40% improvement of the
throughput when compared the common input buffer design method.
Co-Curricular:
First Prize in tennicoit in my college Annual day Celebrations.
Acted as a representative at my schooling and college.
Personal Profile:
Name : D. Rajitha.
Father’s Name : D. Venkateswarlu.
Date of birth : 15th
February, 1993.
Languages known : Telugu, English.
Hobbies : Listening Music.
Address : D-No: 2/83,
JagarlamudiVariPalem (Vill),
Muppavaram (Post),
Addanki-523201,
Prakasam (Dist).
Declaration:
I hereby declare that the information furnished above is true to the best of my
knowledge.
Place: Hyderabad. Yours Sincerely,
Date: (D.RAJITHA)