A Word Embedding-Based Method for Unsupervised Adaptation of Cooking Recipes

A Case-Based Reasoning System for Recommending Cooking Recipes

Nonlinear Embedding Transform for Unsupervised Domain Adaptation

The problem of domain adaptation (DA) deals with adapting classifier models trained on one data distribution to different data distributions. In this paper, we introduce the Nonlinear Embedding Transform (NET) for unsupervised DA by combining domain alignment along with similarity-based embedding. We also introduce a validation procedure to estimate the model parameters for the NET algorithm us...

Conversational Retrieval of Cooking Recipes

This paper presents a new approach for exploring a collection of cooking recipes represented as cooking workflows by means of a conversation. Users are guided through the search process by answering posed questions. Thus, they are not required to formulate queries and they do not need to browse a recipe collection by hand. Questions involve ingredients and cooking activities contained in the wo...

CookingCAKE: A Framework for the Adaptation of Cooking Recipes Represented as Workflows

This paper presents CookingCAKE, a framework for the adaptation of cooking recipes represented as workflows. CookingCAKE integrates and combines several workflow adaptation approaches applied in process-oriented case based reasoning (POCBR) in a single adaptation framework, thus providing a capable tool for the adaptation of cooking recipes. The available case base of cooking workflows is analy...

Hierarchical Recursive Tagset for Annotating Cooking Recipes

Several natural language annotation schemas have been proposed for different natural language understanding tasks. In this paper we present a hierarchical and recursive tagset for annotating natural language recipes. Our recipe annotation tagset is developed to capture both syntactic and semantic information in the text. First, we propose our hierarchical recursive tagset that captures cooking ...