TY - GEN
T1 - Programming bots by synthesizing natural language expressions into API invocations
AU - Zamanirad, Shayan
AU - Benatallah, Boualem
AU - Barukh, Moshe Chai
AU - Casati, Fabio
AU - Rodriguez, Carlos
PY - 2017/11/20
Y1 - 2017/11/20
N2 - At present, bots are still in their preliminary stages of development. Many are relatively simple, or developed ad-hoc for a very specific use-case. For this reason, they are typically programmed manually, or utilize machine-learning classifiers to interpret a fixed set of user utterances. In reality, real world conversations with humans require support for dynamically capturing users expressions. Moreover, bots will derive immeasurable value by programming them to invoke APIs for their results. Today, within the Web and Mobile development community, complex applications are being stringed together with a few lines of code - all made possible by APIs. Yet, developers today are not as empowered to program bots in much the same way. To overcome this, we introduce BotBase, a bot programming platform that dynamically synthesizes natural language user expressions into API invocations. Our solution is two faceted: Firstly, we construct an API knowledge graph to encode and evolve APIs; secondly, leveraging the above we apply techniques in NLP, ML and Entity Recognition to perform the required synthesis from natural language user expressions into API calls.
AB - At present, bots are still in their preliminary stages of development. Many are relatively simple, or developed ad-hoc for a very specific use-case. For this reason, they are typically programmed manually, or utilize machine-learning classifiers to interpret a fixed set of user utterances. In reality, real world conversations with humans require support for dynamically capturing users expressions. Moreover, bots will derive immeasurable value by programming them to invoke APIs for their results. Today, within the Web and Mobile development community, complex applications are being stringed together with a few lines of code - all made possible by APIs. Yet, developers today are not as empowered to program bots in much the same way. To overcome this, we introduce BotBase, a bot programming platform that dynamically synthesizes natural language user expressions into API invocations. Our solution is two faceted: Firstly, we construct an API knowledge graph to encode and evolve APIs; secondly, leveraging the above we apply techniques in NLP, ML and Entity Recognition to perform the required synthesis from natural language user expressions into API calls.
UR - http://www.scopus.com/inward/record.url?scp=85041448452&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85041448452&partnerID=8YFLogxK
U2 - 10.1109/ASE.2017.8115694
DO - 10.1109/ASE.2017.8115694
M3 - Conference contribution
AN - SCOPUS:85041448452
T3 - ASE 2017 - Proceedings of the 32nd IEEE/ACM International Conference on Automated Software Engineering
SP - 832
EP - 837
BT - ASE 2017 - Proceedings of the 32nd IEEE/ACM International Conference on Automated Software Engineering
A2 - Nguyen, Tien N.
A2 - Rosu, Grigore
A2 - Di Penta, Massimiliano
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 32nd IEEE/ACM International Conference on Automated Software Engineering, ASE 2017
Y2 - 30 October 2017 through 3 November 2017
ER -