Exploratory Search with Sentence Embeddings
This work addresses exploratory search for users needing guidance through corpora, but it is incremental as it builds on existing embedding methods without major innovations.
The authors tackled exploratory search by proposing a system using hierarchical clusters and document summaries based on sentence embeddings, and they evaluated it by scraping personal search history and reporting their experience.
Exploratory search aims to guide users through a corpus rather than pinpointing exact information. We propose an exploratory search system based on hierarchical clusters and document summaries using sentence embeddings. With sentence embeddings, we represent documents as the mean of their embedded sentences, extract summaries containing sentences close to this document representation and extract keyphrases close to the document representation. To evaluate our search system, we scrape our personal search history over the past year and report our experience with the system. We then discuss motivating use cases of an exploratory search system of this nature and conclude with possible directions of future work.