ULYSSES: Automated FreqUentLY ASked QueStions for KnowlEdge GraphS

The exponential growth of Knowledge Graphs necessitates effective and efficient methods for their exploration and understanding. Frequently Asked Questions (FAQ) is a service that typically presents a list of questions and answers related to a specific topic, and which is intended to help people understand that topic. Although FAQ has already shown its value on large websites and is widely used, to the best of our knowledge it has not yet been exploited for Knowledge Graphs. In this paper, we present ULYSSES, the first system for automatically constructing FAQ lists for large Knowledge Graphs. Our method consists of three key steps. First, we select the most frequent queries by exploiting the available query logs. Next, we answer the selected queries, using the original graph. Finally, we construct textual descriptions of both the queries and the corresponding answers, exploring state-of-the-art transformer models, i.e., ChatGPT 3.5 and Gemini 1.5 Pro. We evaluate the results of each model, using a human-constructed FAQ list, contributing a unique dataset to the domain and showing the benefits of our approach.

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Publication Details

Journal
Applied Sciences
Published
2024-08-29
DOI
https://doi.org/10.3390/app14177640
Primary Topic
Advanced Graph Neural Networks
Type
article
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article

ULYSSES: Automated FreqUentLY ASked QueStions for KnowlEdge GraphS

Giannis Vassiliou, N. Oikonomou, Nikos Papadakis, Georgia Troullinou et al.
Applied Sciences
Advanced Graph Neural Networks
article

ULYSSES: Automated FreqUentLY ASked QueStions for KnowlEdge GraphS

Giannis Vassiliou, N. Oikonomou, Nikos Papadakis, Georgia Troullinou, Haridimos Kondylakis, Georgia Eirini Trouli, Emmanouil Makaronas, Georgios Pronoitis, Stamatios Kostopoulos, Nikolaos Vlassis, Eleftheria Sfinarolaki, Fotini Droumalia, Georgia Skouteli, Vardis Daskalakis, Iakovos Giannakos, George Bitzarakis, Yiannis Kazantzakis, Argyro Stamatoukou, Nikolaos Spyridakis, Antonis Karagiannakis, Dimitra Deka, Konstantinos Alexandris
article en

Abstract

The exponential growth of Knowledge Graphs necessitates effective and efficient methods for their exploration and understanding. Frequently Asked Questions (FAQ) is a service that typically presents a list of questions and answers related to a specific topic, and which is intended to help people understand that topic. Although FAQ has already shown its value on large websites and is widely used, to the best of our knowledge it has not yet been exploited for Knowledge Graphs. In this paper, we present ULYSSES, the first system for automatically constructing FAQ lists for large Knowledge Graphs. Our method consists of three key steps. First, we select the most frequent queries by exploiting the available query logs. Next, we answer the selected queries, using the original graph. Finally, we construct textual descriptions of both the queries and the corresponding answers, exploring state-of-the-art transformer models, i.e., ChatGPT 3.5 and Gemini 1.5 Pro. We evaluate the results of each model, using a human-constructed FAQ list, contributing a unique dataset to the domain and showing the benefits of our approach.

Applied SciencesVol. 14(17)
University of Crete (GR), Hellenic Mediterranean University (GR), Foundation for Research and Technology Hellas (GR)
Quality Education
Openalex Percentile: Top 88%
Advanced Graph Neural Networks
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