Semantic Web Prefetching Using Semantic Relatedness between Web pages
June 28, 2017 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Jyotsna Parmar, Jyoti
arXiv ID
1706.09206
Category
cs.IR: Information Retrieval
Citations
0
Venue
arXiv.org
Last Checked
4 months ago
Abstract
Internet as become the way of life in the fast growing digital life.Even with the increase in the internet speed, higher latency time is still a challenge. To reduce latency, caching and pre fetching techniques can be used. However, caching fails for dynamic websites which keeps on changing rapidly. Another technique is web prefetching, which prefetches the web pages that the user is likely to request for in the future. Semantic web prefetching makes use of keywords and descriptive texts like anchor text, titles, text surrounding anchor text of the present web pages for predicting users future requests. Semantic information is embedded within the web pages during their designing for the purpose of reflecting the relationship between the web pages. The client can fetch this information from the server. However, this technique involves load on web designers for adding external tags and on server for providing this information along with the desired page, which is not desirable. This paper is an effort to find the semantic relation between web pages using the keywords provided by the user and the anchor texts of the hyperlinks on the present web page.It provides algorithms for sequential and similar semantic relations. These algorithms will be implemented on the client side which will not cause overhead on designers and load on server for semantic information.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Information Retrieval
R.I.P.
π»
Ghosted
π
π
Old Age
Neural Graph Collaborative Filtering
R.I.P.
π»
Ghosted
DeepFM: A Factorization-Machine based Neural Network for CTR Prediction
R.I.P.
π»
Ghosted
BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer
R.I.P.
π
404 Not Found
Graph Neural Networks for Social Recommendation
R.I.P.
π»
Ghosted
Personalized Top-N Sequential Recommendation via Convolutional Sequence Embedding
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
Federated Learning: Strategies for Improving Communication Efficiency
R.I.P.
π»
Ghosted
In-Datacenter Performance Analysis of a Tensor Processing Unit
R.I.P.
π»
Ghosted
Deep Convolutional Neural Networks for Computer-Aided Detection: CNN Architectures, Dataset Characteristics and Transfer Learning
R.I.P.
π»
Ghosted