scholarly journals An Update-Efficient, Disk-Based Inverted Index Structure for Keyword Search on Data Streams

2016 ◽  
Vol 5 (4) ◽  
pp. 171-180
Author(s):  
Eun Ju Park ◽  
Ki Yong Lee
Keyword(s):  
Data Streams ◽  
Keyword Search ◽  
Inverted Index ◽  
Index Structure

scholarly journals HII: Histogram Inverted Index For Fast Images Retrieval

2018 ◽  
Vol 8 (5) ◽  
pp. 3140 ◽  
Author(s):  
Yuda Munarko ◽  
Agus Eko Minarno
Keyword(s):  
Real Number ◽  
Text Retrieval ◽  
Title Page ◽  
Inverted Index ◽  
Index Structure ◽  
Indexing Structure

<div class="page" title="Page 1"><div class="layoutArea"><div class="column"><div class="page" title="Page 1"><div class="layoutArea"><div class="column"><p><span>This work aims to improve the speed of search by creating an indexing structure in CBIR system. We utilised an inverted index structure that usually used in text retrieval with a modification. The modified inverted index is built based on histogram data that generated using Multi Texton Histogram (MTH) and Multi Texton Co-Occurrence Descriptor (MTCD) from 10,000 images of Corel dataset. When building the inverted index, we normalised value of each feature into a real number and considered pairs of feature and value that owned by a particular number of images. Based on our investigation, on MTCD histogram of 5,000 data test, we found that by considering histogram variable values which owned by maximum 12% of images, the number of comparison for each query can be reduced by 67.47% in a rate, the precision is 82.2%, and the rate of access to disk is 32.83%. Furthermore, we named our approach as Histogram Inverted Index (HII). </span></p></div></div></div></div></div></div>

scholarly journals Scalable keyword search over relational data streams by aggressive candidate network consolidation

2019 ◽  
Vol 81 ◽  
pp. 117-135 ◽  
Author(s):  
Savong Bou ◽  
Toshiyuki Amagasa ◽  
Hiroyuki Kitagawa
Keyword(s):  
Data Streams ◽  
Keyword Search ◽  
Relational Data ◽  
Candidate Network

DMSE: Dynamic Multi-keyword Search Encryption based on inverted index

2021 ◽  
pp. 102255
Author(s):  
Yanrong Liang ◽  
Yanping Li ◽  
Kai Zhang ◽  
Lina Ma
Keyword(s):  
Keyword Search ◽  
Inverted Index

scholarly journals Tree-Based Public Key Encryption with Conjunctive Keyword Search

2021 ◽  
Vol 2021 ◽  
pp. 1-16
Author(s):  
Yu Zhang ◽  
Lei You ◽  
Yin Li
Keyword(s):  
Keyword Search ◽  
Public Key ◽  
Index Structure ◽  
Experimental Result ◽  
Public Key Encryption ◽  
Practical Applications ◽  
Result Show ◽  
Searchable Public Key Encryption ◽  
Predicate Encryption ◽  
Index Tree

Searchable public key encryption supporting conjunctive keyword search is an important technique in today’s cloud environment. Nowadays, previous schemes usually take advantage of forward index structure, which leads to a linear search complexity. In order to obtain better search efficiency, in this paper, we utilize a tree index structure instead of forward index to realize such schemes. To achieve the goal, we first give a set of keyword conversion methods that can convert the index and query keywords into a group of vectors and then present a novel algorithm for building index tree based on these vectors. Finally, by combining an efficient predicate encryption scheme to encrypt the index tree, a tree-based public key encryption with conjunctive keyword search scheme is proposed. The proposed scheme is proven to be secure against chosen plaintext attacks and achieves a sublinear search complexity. Moreover, both theoretical analysis and experimental result show that the proposed scheme is efficient and feasible for practical applications.

Efficient fuzzy keyword search scheme over encrypted data in cloud computing based on Bed-tree index structure

2021 ◽  
pp. 1-13
Author(s):  
Dongping Hu ◽  
Aihua Yin
Keyword(s):  
Cloud Computing ◽  
Keyword Search ◽  
Hamming Distance ◽  
Security Analysis ◽  
Index Structure ◽  
Search Performance ◽  
Encrypted Data ◽  
Fuzzy Keyword Search ◽  
Work Security ◽  
And Performance

In cloud computing, enabling search directly over encrypted data is an important technique to effectively utilize encrypted data. Most of the existing techniques are focusing on fuzzy keyword search as it helps achieve more robust search performance by tolerating misspelling or typos of data users. Existing works always build index without classifying keywords in advance. They suffer from efficiency issue. Furthermore, Euclidean distance or Hamming distance is often chosen to evaluate strings’ similarity, ignoring prefixes matching and the influence of strings’ length on the accuracy. We propose an efficient fuzzy keyword search scheme with lower computation cost and higher accuracy to address the aforementioned problems. We employ the sub-dictionaries technique and the Bed-tree structure to build an index with three layers for achieving better search efficiency. With this index structure, the server could locate the keyword and could narrow the search scope quickly. The Jaro-Winkler distance is introduced to qualify the strings’ similarity by considering the prefixes matching and string length. The secure privacy mechanism is incorporated into the design of our work. Security analysis and performance evaluation demonstrate our scheme is more efficient compared to the existing one while guaranteeing security.

Foundation of Keyword Search in XML

2013 ◽  
pp. 1-16
Author(s):  
Weidong Yang ◽  
Hao Zhu
Keyword(s):  
Common Ancestor ◽  
Keyword Search ◽  
Query Languages ◽  
Search Algorithms ◽  
The Other ◽  
Inverted Index ◽  
Xml Database ◽  
Xml Keyword Search ◽  
Lowest Common Ancestor ◽  
Structured Information

It has become desirable to provide a way of keyword search for users to query structured information in an XML database (data-centric retrieval) by combining database and information retrieval techniques. Therefore, the key challenges of keyword search in the XML database are how to define appropriate result models meeting user’s search intents, how to search the results by using efficient algorithms, and how to ranking the results. In this chapter, on one hand, the authors present the foundational knowledge of XML keyword search such as XML data models, XML query languages, inverted index, and Dewey encoding. On the other hand, some existing typical researches of keyword search in XML are presented, including the results models such as Smallest Lowest Common Ancestor (SLCA), Exclusive Lowest Common Ancestor (ELCA), Meaningful Lowest Common Ancestor (MLCA), the related search algorithms, and the ranking approaches.

Keyword Search Mechanisms in Geo-Spatial Databases

2018 ◽  
pp. 176-194
Author(s):  
Priya M. ◽  
Kalpana R.
Keyword(s):  
Spatial Databases ◽  
Keyword Search ◽  
Database Systems ◽  
Index Structure ◽  
Hybrid Index ◽  
Spatial Objects ◽  
Ranking Model ◽  
Text Information ◽  
Spatial Indexes ◽  
The Given

Most web and mobile applications are based on searching the location-based objects called spatial objects. In spatial database systems, searching such objects is a challenging task since it deals with geo-spatial capabilities. Sometimes, the spatial queries are associated with text information in order to obtain the most relevant answers nearest to the given location. Such queries are called spatial textual query. Conventional spatial indexes and text indexes are not suitable for resolving such queries. Since these indexes use various approaches to perform searching, they can cause performance degradation. Effective processing of the query mainly depends on the index structure, searching algorithms, and location-based ranking. This chapter reviews the different hybrid index structures and search mechanisms to extract the spatial objects, the different ranking model it supports, and the performance characteristics.

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