TY - GEN
T1 - Social media based NPL system to find and retrieve ARM data
T2 - 5th IEEE International Conference on Big Data, Big Data 2017
AU - Devarakonda, Ranjeet
AU - Giansiracusa, Michael
AU - Kumar, Jitendra
AU - Shanafield, Harold
N1 - Publisher Copyright:
© 2017 IEEE.
PY - 2017/7/1
Y1 - 2017/7/1
N2 - Information connectivity and retrieval has a role in our daily lives. The most pervasive source of online information is databases. The amount of data is growing at rapid rate and database technology is improving and having a profound effect. Almost all online applications are storing and retrieving information from databases. One challenge in supplying the public with wider access to informational databases is the need for knowledge of database languages like Structured Query Language (SQL). Although the SQL language has been published in many forms, not everybody is able to write SQL queries. Another challenge is that it may not be practical to make the public aware of the structure of the database. There is a need for novice users to query relational databases using their natural language. To solve this problem, many natural language interfaces to structured databases have been developed. The goal is to provide more intuitive method for generating database queries and delivering responses. Social media makes it possible to interact with a wide section of the population. Through this medium, and with the help of Natural Language Processing (NLP) we can make the data of the Atmospheric Radiation Measurement Data Center (ADC) more accessible to the public. We propose an architecture for using Apache Lucene/Solr [1], OpenML [2,3], and Kafka [4] to generate an automated query/response system with inputs from Twitter5, our Cassandra DB, and our log database. Using the Twitter API and NLP we can give the public the ability to ask questions of our database and get automated responses.
AB - Information connectivity and retrieval has a role in our daily lives. The most pervasive source of online information is databases. The amount of data is growing at rapid rate and database technology is improving and having a profound effect. Almost all online applications are storing and retrieving information from databases. One challenge in supplying the public with wider access to informational databases is the need for knowledge of database languages like Structured Query Language (SQL). Although the SQL language has been published in many forms, not everybody is able to write SQL queries. Another challenge is that it may not be practical to make the public aware of the structure of the database. There is a need for novice users to query relational databases using their natural language. To solve this problem, many natural language interfaces to structured databases have been developed. The goal is to provide more intuitive method for generating database queries and delivering responses. Social media makes it possible to interact with a wide section of the population. Through this medium, and with the help of Natural Language Processing (NLP) we can make the data of the Atmospheric Radiation Measurement Data Center (ADC) more accessible to the public. We propose an architecture for using Apache Lucene/Solr [1], OpenML [2,3], and Kafka [4] to generate an automated query/response system with inputs from Twitter5, our Cassandra DB, and our log database. Using the Twitter API and NLP we can give the public the ability to ask questions of our database and get automated responses.
KW - machine learning
KW - natural language processing
KW - social media interaction
KW - stream pipelining
UR - http://www.scopus.com/inward/record.url?scp=85047757632&partnerID=8YFLogxK
U2 - 10.1109/BigData.2017.8258525
DO - 10.1109/BigData.2017.8258525
M3 - Conference contribution
AN - SCOPUS:85047757632
T3 - Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017
SP - 4736
EP - 4737
BT - Proceedings - 2017 IEEE International Conference on Big Data, Big Data 2017
A2 - Nie, Jian-Yun
A2 - Obradovic, Zoran
A2 - Suzumura, Toyotaro
A2 - Ghosh, Rumi
A2 - Nambiar, Raghunath
A2 - Wang, Chonggang
A2 - Zang, Hui
A2 - Baeza-Yates, Ricardo
A2 - Baeza-Yates, Ricardo
A2 - Hu, Xiaohua
A2 - Kepner, Jeremy
A2 - Cuzzocrea, Alfredo
A2 - Tang, Jian
A2 - Toyoda, Masashi
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 11 December 2017 through 14 December 2017
ER -