Multi-Term Semantic Context Elicitation from Collaborative Networks

Paolo Mengoni; Alfredo Milani; Yuanxi Li

doi:10.1109/AIKE.2018.00053

Multi-Term Semantic Context Elicitation from Collaborative Networks

Paolo Mengoni, Alfredo Milani, Yuanxi Li

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

3 Citations (Scopus)

Abstract

In this work we present an innovative approach to the semantic context elicitation among a set of terms. Topic and context elicitation using semantic features can be applied to query expansion, natural language processing, and multimedia retrieval. Different techniques rely on web objects to extract information considering the direct semantic relationship between the observed objects. In our approach we explore the Wikipedia collaborative network to extract the pairwise semantic chains. The terms that constitute all the pairwise chains will define the context in which the set of terms are immersed. Traversal, graph and Steiner tree analysis are evaluated by experts. Results are encouraging and experts agree that the Steiner tree analysis conveys additional semantic information about the relationship among the words in the context.

Original language	English
Title of host publication	Proceedings - 2018 1st IEEE International Conference on Artificial Intelligence and Knowledge Engineering, AIKE 2018
Publisher	IEEE
Pages	234-238
Number of pages	5
ISBN (Electronic)	9781538695555
ISBN (Print)	9781538695562
DOIs	https://doi.org/10.1109/AIKE.2018.00053
Publication status	Published - Sept 2018
Event	1st IEEE International Conference on Artificial Intelligence and Knowledge Engineering, AIKE 2018 - Laguna Hills, United States Duration: 26 Sept 2018 → 28 Sept 2018

Publication series

Name	Proceedings - IEEE International Conference on Artificial Intelligence and Knowledge Engineering, AIKE

Conference

Conference	1st IEEE International Conference on Artificial Intelligence and Knowledge Engineering, AIKE 2018
Country/Territory	United States
City	Laguna Hills
Period	26/09/18 → 28/09/18

User-Defined Keywords

Heuristic search
Random walk
Semantic context
Steiner trees
Wikipedia

Access to Document

10.1109/AIKE.2018.00053

Cite this

Mengoni, P., Milani, A., & Li, Y. (2018). Multi-Term Semantic Context Elicitation from Collaborative Networks. In Proceedings - 2018 1st IEEE International Conference on Artificial Intelligence and Knowledge Engineering, AIKE 2018 (pp. 234-238). (Proceedings - IEEE International Conference on Artificial Intelligence and Knowledge Engineering, AIKE). IEEE. https://doi.org/10.1109/AIKE.2018.00053

@inproceedings{22b912430bbc423bba7f219fd526daf0,

title = "Multi-Term Semantic Context Elicitation from Collaborative Networks",

abstract = "In this work we present an innovative approach to the semantic context elicitation among a set of terms. Topic and context elicitation using semantic features can be applied to query expansion, natural language processing, and multimedia retrieval. Different techniques rely on web objects to extract information considering the direct semantic relationship between the observed objects. In our approach we explore the Wikipedia collaborative network to extract the pairwise semantic chains. The terms that constitute all the pairwise chains will define the context in which the set of terms are immersed. Traversal, graph and Steiner tree analysis are evaluated by experts. Results are encouraging and experts agree that the Steiner tree analysis conveys additional semantic information about the relationship among the words in the context.",

keywords = "Heuristic search, Random walk, Semantic context, Steiner trees, Wikipedia",

author = "Paolo Mengoni and Alfredo Milani and Yuanxi Li",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 1st IEEE International Conference on Artificial Intelligence and Knowledge Engineering, AIKE 2018 ; Conference date: 26-09-2018 Through 28-09-2018",

year = "2018",

month = sep,

doi = "10.1109/AIKE.2018.00053",

language = "English",

isbn = "9781538695562",

series = "Proceedings - IEEE International Conference on Artificial Intelligence and Knowledge Engineering, AIKE",

publisher = "IEEE",

pages = "234--238",

booktitle = "Proceedings - 2018 1st IEEE International Conference on Artificial Intelligence and Knowledge Engineering, AIKE 2018",

address = "United States",

}

Mengoni, P, Milani, A & Li, Y 2018, Multi-Term Semantic Context Elicitation from Collaborative Networks. in Proceedings - 2018 1st IEEE International Conference on Artificial Intelligence and Knowledge Engineering, AIKE 2018. Proceedings - IEEE International Conference on Artificial Intelligence and Knowledge Engineering, AIKE, IEEE, pp. 234-238, 1st IEEE International Conference on Artificial Intelligence and Knowledge Engineering, AIKE 2018, Laguna Hills, United States, 26/09/18. https://doi.org/10.1109/AIKE.2018.00053

Multi-Term Semantic Context Elicitation from Collaborative Networks. / Mengoni, Paolo; Milani, Alfredo; Li, Yuanxi.
Proceedings - 2018 1st IEEE International Conference on Artificial Intelligence and Knowledge Engineering, AIKE 2018. IEEE, 2018. p. 234-238 (Proceedings - IEEE International Conference on Artificial Intelligence and Knowledge Engineering, AIKE).

Research output: Chapter in book/report/conference proceeding › Conference proceeding › peer-review

TY - GEN

T1 - Multi-Term Semantic Context Elicitation from Collaborative Networks

AU - Mengoni, Paolo

AU - Milani, Alfredo

AU - Li, Yuanxi

PY - 2018/9

Y1 - 2018/9

N2 - In this work we present an innovative approach to the semantic context elicitation among a set of terms. Topic and context elicitation using semantic features can be applied to query expansion, natural language processing, and multimedia retrieval. Different techniques rely on web objects to extract information considering the direct semantic relationship between the observed objects. In our approach we explore the Wikipedia collaborative network to extract the pairwise semantic chains. The terms that constitute all the pairwise chains will define the context in which the set of terms are immersed. Traversal, graph and Steiner tree analysis are evaluated by experts. Results are encouraging and experts agree that the Steiner tree analysis conveys additional semantic information about the relationship among the words in the context.

AB - In this work we present an innovative approach to the semantic context elicitation among a set of terms. Topic and context elicitation using semantic features can be applied to query expansion, natural language processing, and multimedia retrieval. Different techniques rely on web objects to extract information considering the direct semantic relationship between the observed objects. In our approach we explore the Wikipedia collaborative network to extract the pairwise semantic chains. The terms that constitute all the pairwise chains will define the context in which the set of terms are immersed. Traversal, graph and Steiner tree analysis are evaluated by experts. Results are encouraging and experts agree that the Steiner tree analysis conveys additional semantic information about the relationship among the words in the context.

KW - Heuristic search

KW - Random walk

KW - Semantic context

KW - Steiner trees

KW - Wikipedia

UR - http://www.scopus.com/inward/record.url?scp=85058212185&partnerID=8YFLogxK

U2 - 10.1109/AIKE.2018.00053

DO - 10.1109/AIKE.2018.00053

M3 - Conference proceeding

AN - SCOPUS:85058212185

SN - 9781538695562

T3 - Proceedings - IEEE International Conference on Artificial Intelligence and Knowledge Engineering, AIKE

SP - 234

EP - 238

BT - Proceedings - 2018 1st IEEE International Conference on Artificial Intelligence and Knowledge Engineering, AIKE 2018

PB - IEEE

T2 - 1st IEEE International Conference on Artificial Intelligence and Knowledge Engineering, AIKE 2018

Y2 - 26 September 2018 through 28 September 2018

ER -

Mengoni P, Milani A, Li Y. Multi-Term Semantic Context Elicitation from Collaborative Networks. In Proceedings - 2018 1st IEEE International Conference on Artificial Intelligence and Knowledge Engineering, AIKE 2018. IEEE. 2018. p. 234-238. (Proceedings - IEEE International Conference on Artificial Intelligence and Knowledge Engineering, AIKE). doi: 10.1109/AIKE.2018.00053

Multi-Term Semantic Context Elicitation from Collaborative Networks

Abstract

Publication series

Conference

User-Defined Keywords

Access to Document

Other files and links

Fingerprint

Cite this