scholarly journals Document Retrieval and Ranking using Similarity Graph Mean Hitting Times.

2021 ◽  
Author(s):  
Daniel Dunlavy ◽  
Peter Chew
2020 ◽  
Vol 4 (3) ◽  
pp. 551-557
Author(s):  
Muhammad zaky ramadhan ◽  
Kemas Muslim Lhaksmana

Hadith has several levels of authenticity, among which are weak (dhaif), and fabricated (maudhu) hadith that may not originate from the prophet Muhammad PBUH, and thus should not be considered in concluding an Islamic law (sharia). However, many such hadiths have been commonly confused as authentic hadiths among ordinary Muslims. To easily distinguish such hadiths, this paper proposes a method to check the authenticity of a hadith by comparing them with a collection of fabricated hadiths in Indonesian. The proposed method applies the vector space model and also performs spelling correction using symspell to check whether the use of spelling check can improve the accuracy of hadith retrieval, because it has never been done in previous works and typos are common on Indonesian-translated hadiths on the Web and social media raw text. The experiment result shows that the use of spell checking improves the mean average precision and recall to become 81% (from 73%) and 89% (from 80%), respectively. Therefore, the improvement in accuracy by implementing spelling correction make the hadith retrieval system more feasible and encouraged to be implemented in future works because it can correct typos that are common in the raw text on the Internet.


Shore & Beach ◽  
2020 ◽  
pp. 92-101
Author(s):  
Richard Raynie ◽  
Syed Khalil ◽  
Charles Villarrubia ◽  
Ed Haywood

The Coastal Protection and Restoration Authority (CPRA) of Louisiana was created after the devastating hurricanes of 2005 (Katrina and Rita) and is responsible for planning and implementing projects that will either reduce storm-induced losses (protection) or restore coastal ecosystems that have been lost or are in danger of being lost (restoration). The first task of the CPRA board was to develop Louisiana’s first Coastal Master Plan (CPRA 2007), which formally integrates and guides the protection and restoration of Louisiana’s coast. The System-Wide Assessment and Monitoring Program (SWAMP) was subsequently developed as a long-term monitoring program to ensure that a comprehensive network of coastal data collection activities is in place to support the planning, development, implementation, and adaptive management of the protection and restoration program and projects within coastal Louisiana. SWAMP includes both natural-system and human-system components and also incorporates the previously-developed Coastwide Reference Monitoring System (CRMS), the Barrier Island Comprehensive Monitoring (BICM) program, and fisheries data collected by the Louisiana Department of Wildlife and Fisheries (LDWF) in addition to other aspects of system dynamics, including offshore and inland water-body boundary conditions, water quality, risk status, and protection performance, which have historically not been the subject of CPRA-coordinated monitoring. This program further facilitates the integration of project-specific data needs into a larger, system-level design framework. Monitoring and operation of restoration and protection projects will be nested within a larger hydrologic basin-wide and coast-wide SWAMP framework and will allow informed decisions to be made with an understanding of system conditions and dynamics at multiple scales. This paper also provides an update on the implementation of various components of SWAMP in Coastal Louisiana, which began as a Barataria Basin pilot implementation program in 2015. During 2017, the second phase of SWAMP was initiated in the areas east of the Mississippi River. In 2019, development of SWAMP design was completed for the remaining basins in coastal Louisiana west of Bayou Lafourche (Figure 1). Data collection is important to inform decisions, however if the data are not properly managed or are not discoverable, they are of limited use. CPRA is committed to ensuring that information is organized and publicly available to help all coastal stakeholders make informed, science-based decisions. As a part of this effort, CPRA has re-engineered its data management system to include spatial viewers, tabular download web pages, and a library/document retrieval system along with a suite of public-facing web services providing programmatic access. This system is collectively called the Coastal Information Management System (CIMS). CPRA and U.S. Geological Survey (USGS) are also developing a proposal to create an interface for CIMS data to be exported to a neutral template that could then be ingested into NOAA’s Data Integration Visualization, Exploration and Reporting (DIVER) repository, and vice versa. DIVER is the repository that the Natural Resource Damage Assessment (NRDA) program is using to manage NRDA-funded project data throughout the Gulf of Mexico. Linking CIMS and DIVER will make it easier to aggregate data across Gulf states and look at larger, ecosystem-level changes.


2021 ◽  
pp. 016555152110184
Author(s):  
Gunjan Chandwani ◽  
Anil Ahlawat ◽  
Gaurav Dubey

Document retrieval plays an important role in knowledge management as it facilitates us to discover the relevant information from the existing data. This article proposes a cluster-based inverted indexing algorithm for document retrieval. First, the pre-processing is done to remove the unnecessary and redundant words from the documents. Then, the indexing of documents is done by the cluster-based inverted indexing algorithm, which is developed by integrating the piecewise fuzzy C-means (piFCM) clustering algorithm and inverted indexing. After providing the index to the documents, the query matching is performed for the user queries using the Bhattacharyya distance. Finally, the query optimisation is done by the Pearson correlation coefficient, and the relevant documents are retrieved. The performance of the proposed algorithm is analysed by the WebKB data set and Twenty Newsgroups data set. The analysis exposes that the proposed algorithm offers high performance with a precision of 1, recall of 0.70 and F-measure of 0.8235. The proposed document retrieval system retrieves the most relevant documents and speeds up the storing and retrieval of information.


2021 ◽  
Vol 1757 (1) ◽  
pp. 012001
Author(s):  
Ni Li ◽  
Manman Peng ◽  
Buwen Cao ◽  
Kenli Li ◽  
Keqin Li

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