{"type":"ScholarlyArticle","title":"Towards Domain-Specific Semantic Relatedness: A Case Study from Geography","authors":[{"name":"Shilad Sen","slug":"shilad-sen","given":"Shilad","family":"Sen","affiliation":""},{"name":"Isaac L. Johnson","slug":"isaac-l-johnson","given":"Isaac L.","family":"Johnson","affiliation":""},{"name":"Rebecca Harper","slug":"rebecca-harper","given":"Rebecca","family":"Harper","affiliation":""},{"name":"Huy Mai","slug":"huy-mai","given":"Huy","family":"Mai","affiliation":""},{"name":"Samuel Horlbeck Olsen","slug":"samuel-horlbeck-olsen","given":"Samuel Horlbeck","family":"Olsen","affiliation":""},{"name":"Benjamin Mathers","slug":"benjamin-mathers","given":"Benjamin","family":"Mathers","affiliation":""},{"name":"Laura Souza Vonessen","slug":"laura-souza-vonessen","given":"Laura Souza","family":"Vonessen","affiliation":""},{"name":"Matthew Wright","slug":"matthew-wright","given":"Matthew","family":"Wright","affiliation":""},{"name":"Brent J. Hecht","slug":"brent-j-hecht","given":"Brent J.","family":"Hecht","affiliation":""}],"abstract":"Semantic relatedness (SR) measures form the algorithmic foundation of intelligent technologies in domains ranging from artificial intelligence to human-computer interaction. Although SR has been researched for decades, this work has focused on developing general SR measures rooted in graph and text mining algorithms that perform reasonably well for many different types of concepts. This paper introduces domain-specific SR, which augments general SR by identifying, capturing, and synthesizing domain-specific relationships between concepts. Using the domain of geography as a case study, we show that domain-specific SR — and even geography-specific signals alone (e.g. distance, containment) without sophisticated graph or text mining algorithms — significantly outperform the SR state-of-the-art for geographic concepts. In addition to substantially improving SR measures for geospatial technologies, an area that is rapidly increasing in importance, this work also unlocks an important new direction for SR research: SR measures that incorporate domain-specific customizations to increase accuracy.","doi":null,"url":"https://ijcai.org/proceedings/2015/334","pdf":"https://ijcai.org/proceedings/2015/0334.pdf","markdown":"https://ijcai.org/proceedings/2015/334.md","bibtex":"https://ijcai.org/proceedings/2015/bibtex/334","volume":{"slug":"2015","title":"Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2015","url":"https://ijcai.org/proceedings/2015/","year":2015,"location":"Buenos Aires, Argentina","dates":"25–31 July 2015","editors":"Qiang Yang and Michael Wooldridge","isbn":"978-1-57735-738-4","publisher":"International Joint Conferences on Artificial Intelligence","doi_prefix":""},"section":"Web Mining","track":"Main Track","number":334,"pages":{"first":2362,"last":2369},"keywords":[],"videos":[],"references":[],"license_note":"Copyright International Joint Conferences on Artificial Intelligence."}