18 citations · 28 across the 11 of their papers we have counts for
12 papers
Recommendation Systems for Exploratory Data Tasks
Anna Fariha, Whanhee Cho
Exploratory Data Tasks (EDTs) involve iteratively steering workflows as users refine their subjective goals based on newly emerging insights. EDTs are performed by millions of user…
ChARLES: Change-Aware Recovery of Latent Evolution Semantics in Relational Data
Shiyi He, Alexandra Meliou, Anna Fariha
Data-driven decision-making is at the core of many modern applications, and understanding the data is critical in supporting trust in these decisions. However, data is dynamic and…
Development of Data Evaluation Benchmark for Data Wrangling Recommendation System
Yuqing Wang, Anna Fariha
CoWrangler is a data-wrangling recommender system designed to streamline data processing tasks. Recognizing that data processing is often time-consuming and complex for novice user…
Conversational Challenges in AI-Powered Data Science: Obstacles, Needs, and Design Opportunities
Bhavya Chopra, Ananya Singha, Anna Fariha +4
Large Language Models (LLMs) are being increasingly employed in data science for tasks like data preprocessing and analytics. However, data scientists encounter substantial obstacl…
Rapidash: Efficient Constraint Discovery via Rapid Verification
Zifan Liu, Shaleen Deep, Anna Fariha +3
Denial Constraint (DC) is a well-established formalism that captures a wide range of integrity constraints commonly encountered, including candidate keys, functional dependencies,…
Neurosymbolic Repair for Low-Code Formula Languages
Rohan Bavishi, Harshit Joshi, José Pablo Cambronero Sánchez +5
Most users of low-code platforms, such as Excel and PowerApps, write programs in domain-specific formula languages to carry out nontrivial tasks. Often users can write most of the…
DataExposer: Exposing Disconnect between Data and Systems
Sainyam Galhotra, Anna Fariha, Raoni Lourenço +3
As data is a central component of many modern systems, the cause of a system malfunction may reside in the data, and, specifically, particular properties of the data. For example,…
Example-Driven User Intent Discovery: Empowering Users to Cross the SQL Barrier Through Query by Example
Anna Fariha, Lucy Cousins, Narges Mahyar +1
Traditional data systems require specialized technical skills where users need to understand the data organization and write precise queries to access data. Therefore, novice users…
Through the Data Management Lens: Experimental Analysis and Evaluation of Fair Classification
Maliha Tashfia Islam, Anna Fariha, Alexandra Meliou +1
Classification, a heavily-studied data-driven machine learning task, drives an increasing number of prediction systems involving critical human decisions such as loan approval and…
Causality-Guided Adaptive Interventional Debugging
Anna Fariha, Suman Nath, Alexandra Meliou
Runtime nondeterminism is a fact of life in modern database applications. Previous research has shown that nondeterminism can cause applications to intermittently crash, become unr…
Conformance Constraint Discovery: Measuring Trust in Data-Driven Systems
Anna Fariha, Ashish Tiwari, Arjun Radhakrishna +2
The reliability and proper function of data-driven applications hinge on the data's continued conformance to the applications' initial design. When data deviates from this initial…
Example-Driven Query Intent Discovery: Abductive Reasoning using Semantic Similarity
Anna Fariha, Alexandra Meliou
Traditional relational data interfaces require precise structured queries over potentially complex schemas. These rigid data retrieval mechanisms pose hurdles for non-expert users,…