Automatic Task Completion Flows from Web APIs

By Kyle Williams, Seyyed Hadi Hashemi, Imed Zitouni. 2019

3 citations recorded by the source corpus.

The Web contains many APIs that could be combined in countless ways to enable Intelligent Assistants to complete all sorts of tasks. We propose a method to automatically produce task completion flows from a collection of these APIs by combining them in a graph and automatically extracting paths from the graph for task completion. These paths chain together API calls and use the output of executed APIs as inputs to others. We automatically extract these paths from an API graph in response to a user query and then rank the paths by the likelihood of them leading to user satisfaction. We apply our approach for task completion in the email and calendar domains and show how it can be used to automatically create task completion flows.

Subfields: Information Systems, Information Systems and Management, Natural Language Processing, Human-Computer Interaction

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Information Systems

1. Huan Sun
2. Karthik Narasimhan
3. Xiang Deng
4. Yu Su
5. Boshi Wang

In Information Systems and Management

1. Huan Sun

In Natural Language Processing

1. Shunyu Yao
2. Karthik Narasimhan
3. John Yang
4. Howard Chen
5. Huan Sun
6. Xiang Deng
7. Yu Su
8. Yu Gu

In Human-Computer Interaction

1. Karthik Narasimhan

Citations in the corpus

• WebShop: Towards Scalable Real-World Web Interaction with Grounded Language Agents (2022, background): “Various supervised classification tasks on webpages have been proposed, including predicting web elements [39], generating API calls [46, 47, 54] and semantic parsing into concept-level navigation actions [31].”
• FLIN: A Flexible Natural Language Interface for Web Navigation (2020, unknown): “…includes learning tasks from demonstrations (Allen et al., 2007), building reinforcement learning agents (Shi et al., 2017b; Liu et al., 2018b), semantic parsing using seq2seq models to map NL commands into web APIs (Su et al., 2017, 2018) and generating task flows from APIs (Williams et al., 2019).”
• Mind2Web: Towards a Generalist Agent for the Web (2023, methodology): “For example, it may be used as a plugin for ChatGPT [20] to directly acquire information and carry out actions on HTML websites, instead of only retrieving web content through a retriever tool [5, 14] or relying on pre-defined APIs for each web service [30, 33].”