Applying Dewey Encoding to Construct XML Index for Path and Keyword Query

Dwelling in the information age permits nearly everybody needs to recover countless information and choices to gather from to fulfill their necessities. In distinctive cases, the quantity of information accessible and the speed of change may cover the ideal and required explanation. Spatial-textual queries provide the most acclaimed nearest points concerning a conveyed site and a keyword set. Current practice regularly thought on the most capable technique to expertly get the top-k resultset reestablished a spatial-scholarly query. A capable Spatial Range Skyline Query (SRSQ) algorithm is proposed which initially performsa spatial keyword query (SKQ) that relies upon an IRtree that documents the information. Skyline centers picked are not simply established on their partitions to a lot of inquiries and more subject to their significance to a social occasion of query keywords. Additionally, besides proposed range skyline (RS) methods based on R-tree multi-dimensional space including secondary- memory pruning tools for operating field skyline queries is accomplished. The advanced scheme is dynamic and I/O optimum. Ultimately, methodology presents a modern assessment that demonstrates the proficiency.

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Application of an artificial intelligence algorithm model of memory retrieval and roaming in sorting Chinese medicinal materials

Journal of Computational Methods in Sciences and Engineering ◽

10.3233/jcm-215477 ◽

2021 ◽

pp. 1-11

Author(s):

Chengbing Tan ◽

Qun Chen

Keyword(s):

Autobiographical Memory ◽

Memory Retrieval ◽

Memory Search ◽

Middle Layer ◽

Bottom Layer ◽

Human Memory ◽

Keyword Query ◽

Retrieval Cues ◽

Artificial Intelligence Algorithm ◽

Response Performance

In order to capture autobiographical memory, inspired by the development of human intelligence, a computational AM model for autobiographical memory is proposed in this paper, which is a three-layer network structure, in which the bottom layer encodes the event-specific knowledge comprising 5W1H, and provides retrieval clues to the middle layer, encodes the related events, and the top layer encodes the event set. According to the bottom-up memory search process, the corresponding events and event sets can be identified in the middle layer and the top layer respectively; At the same time, AM model can simulate human memory roaming through the process of rule-based memory retrieval. The computational AM model proposed in this paper not only has robust and flexible memory retrieval, but also has better response performance to noisy memory retrieval cues than the commonly used memory retrieval model based on keyword query method, and can also imitate the roaming phenomenon in memory.

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