Abstract
The Web search engines have been instrumental in providing information from all over the globe to the user. The advent of the Web search engines has resulted in obtaining the relevant information at the user's location. The central theme of all Web search engines is to provide the relevant information expected by the user. To address this issue, many sophisticated ranking functions have been developed, which rank the documents based on their relevance to the user's query. The ranking component is one of the most important components for designing Web object search engines. This component helps in contributing toward the activeness of Web object search engine w.r.t. user relevance. Designing of active result ranking functions, which also considers the geographical proximity of the queries, is extremely important to provide user relevant results.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Carpineto C, Romano G, Giannini V (2002) Improving retrieval feedback with multiple term-ranking function combination. ACM Trans Inf Syst (TOIS) 20(3):259–290
Callan P (2000) Distributed Information retrieval. In: Bruce Croft W (ed) Advances in information retrieval. Recent research from the center for intelligent information retrieval. Kluwer Academic Publisher, pp 127–150
Anjan Kumar KN, Chitra S, Satish Kumar T (2019) Probabilistic classification techniques to perform geographical labeling of web objects. Cluster Comput 22(1):277–285
He B, Ounis I (2009) Finding good feedback documents. In: Proceedings of the 18th ACM conference on information and knowledge management. ACM
Natsev AP et al (2007) Semantic concept-based query expansion and re-ranking for multimedia retrieval. In: Proceedings of the 15th ACM international conference on Multimedia. ACM
Davis CA, Fonseca FT (2007) Assessing the certainty of locations produced by an address geocoding system. Geoinformatica 11(1):103–129
Dalton J, Blanco R, Mika P (2011) Coreference aware web object retrieval. In: Proceedings of the 20th ACM international conference on Information and knowledge management. ACM
Chen L et al (2006) Ranking web objects from multiple communities. In: Proceedings of the 15th ACM international conference on information and knowledge management. ACM
Efthimiadis EN (1993) A user-centred evaluation of ranking algorithms for interactive query expansion. In: Proceedings of the 16th annual international ACM SIGIR conference on research and development in information retrieval. ACM
Buyukokkten O et al (1999) Exploiting geographical location information of web pages
Sengar V et al (2007) Robust location search from text queries. In: Proceedings of the 15th annual ACM international symposium on advances in geographic information systems. ACM
Wu D, Cong G, Jensen CS (2012) A framework for efficient spatial web object retrieval. VLDB J 21(6):797–822
Cao G et al (2007) Extending query translation to cross-language query expansion with markov chain models. In: Proceedings of the sixteenth ACM conference on conference on information and knowledge management. ACM
Broder A et al (2009) Online expansion of rare queries for sponsored search. In: Proceedings of the 18th international conference on World wide web. ACM
Fetahu B, Gadiraju U, Dietze S (2015) Improving entity retrieval on structured data. In: International semantic web conference. Springer, Cham
Wu D, Cong G, Jensen CS (2012) A framework for efficient spatial web object retrieval. VLDB J 21(6):797–822
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2021 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Anjan Kumar, K.N., Satish Kumar, T., Krishna Prasad, R., Ravi Kumar, S.G. (2021). Web Object Ranking for Location-Based Web Object Search. In: Agrawal, R., Kishore Singh, C., Goyal, A. (eds) Advances in Smart Communication and Imaging Systems . Lecture Notes in Electrical Engineering, vol 721. Springer, Singapore. https://doi.org/10.1007/978-981-15-9938-5_16
Download citation
DOI: https://doi.org/10.1007/978-981-15-9938-5_16
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-15-9937-8
Online ISBN: 978-981-15-9938-5
eBook Packages: Computer ScienceComputer Science (R0)