scholarly journals Discovering Travel Spatiotemporal Pattern Based on Sequential Events Similarity

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-10
Author(s):  
Juanjuan Chen ◽  
Liying Huang ◽  
Chengliang Wang ◽  
Nijia Zheng
Keyword(s):  
Sequence Similarity ◽  
Social Systems ◽  
Individual Preference ◽  
User Preference ◽  
Spatiotemporal Pattern ◽  
Novel Approach ◽  
Spreading Dynamics ◽  
Route Recommendation ◽  
New City ◽  
Travel Route Recommendation

Travel route preferences can strongly interact with the events that happened in networked traveling, and this coevolving phenomena are essential in providing theoretical foundations for travel route recommendation and predicting collective behaviour in social systems. While most literature puts the focus on route recommendation of individual scenic spots instead of city travel, we propose a novel approach named City Travel Route Recommendation based on Sequential Events Similarity (CTRR-SES) by applying the coevolving spreading dynamics of the city tour networks and mine the travel spatiotemporal patterns in the networks. First, we present the Event Sequence Similarity Measurement Method based on modelling tourists’ travel sequences. The method can help measure similarities in various city travel routes, which combine different scenic types, time slots, and relative locations. Second, by applying the user preference learning method based on scenic type, we learn from the user’s city travel historical data and compute the personalized travel preference. Finally, we verify our algorithm by collecting data of 54 city travellers of their historical spatiotemporal routes in the ten most popular cities from Mafeng.com. CTRR-SES shows better performance in predicting the user’s new city travel sequence fitting the user’s individual preference.

scholarly journals Design and Development of a Real-Time Optimal Route Recommendation System Using Big Data for Tourists in Jeju Island

Electronics ◽  
2019 ◽  
Vol 8 (5) ◽  
pp. 506 ◽  
Author(s):  
Faisal Mehmood ◽  
Shabir Ahmad ◽  
DoHyeun Kim
Keyword(s):  
Big Data ◽  
Real Time ◽  
Recommendation System ◽  
Tourism Industry ◽  
Jeju Island ◽  
Third Party ◽  
User Preference ◽  
Optimal Route ◽  
Route Recommendation ◽  
Travel Route Recommendation

Nowadays researchers and engineers are trying to build travel route recommendation systems to guide tourists around the globe. The tourism industry is on the rise and it has attracted researchers to provide such systems for comfortable and convenient traveling. Mobile internet growth is increasing rapidly. Mobile data usage and traffic growth has increased interest in building mobile applications for tourists. This research paper aims to provide design and implementation of a travel route recommendation system based on user preference. Real-time big data is collected from Wi-Fi routers installed at more than 149 unique locations in Jeju Island, South Korea. This dataset includes tourist movement patterns collected from thousands of mobile tourists in the year 2016–2017. Data collection and analysis is necessary for a country to make public policies and development of the global travel and tourism industry. In this research paper we propose an optimal travel route recommendation system by performing statistical analysis of tourist movement patterns. Route recommendation is based on user preferences. User preference can vary over time and differ from one user to another. We have taken three main factors into consideration to the recommend optimal route i.e., time, distance, and popularity of location. Beside these factors, we have also considered weather and traffic condition using a third-party application program interfaces (APIs). We have classified regions into six major categories. Popularity of location can vary from season to season. We used a Naïve Bayes classifier to find the probability of tourists going to visit next location. Third-party APIs are used to find the longitude and latitude of the location. The Haversine formula is used to calculate the distance between unique locations. On the basis of these factors, we recommend the optimal route for tourists. The proposed system is highly responsive to mobile users. The results of this system show that the recommended route is convenient and allows tourists to visit maximum number of famous locations as compared to previous data.

Research on the Realization of Travel Recommendations for Different Users Through Deep Learning Under Global Information Management

2022 ◽  
Vol 30 (7) ◽  
pp. 0-0
Keyword(s):  
Deep Learning ◽  
Information Management ◽  
User Preference ◽  
Global Information ◽  
Tourist Destinations ◽  
The Past ◽  
Geographic Factor ◽  
Route Recommendation ◽  
Travel Route Recommendation ◽  
Travel Recommendation

This article is mainly to study the realization of travel recommendations for different users through deep learning under global information management. The personalized travel route recommendation is realized by establishing personalized travel dynamic interest (PTDR) algorithm and distributed lock manager (DLM) model. It is hoped that this model can provide more complete data information of tourist destinations on the basis of the past, and can also meet the needs of users. The innovation of this article is to compare and analyze with a large number of baseline algorithms, highlighting the superiority of this model in personalized travel recommendation. In addition, the model incorporates the topic factor features, geographic factor features, and user preference features to make the data more in line with user needs and improve the efficiency and applicability of the model. It is hoped that the plan proposed in this article can help users make choices of tourist destinations more conveniently.

scholarly journals Molecular Identification of Ectomycorrhizal Mycelium in Soil Horizons

2003 ◽  
Vol 69 (1) ◽  
pp. 327-333 ◽  
Author(s):  
Renske Landeweert ◽  
Paula Leeflang ◽  
Thom W. Kuyper ◽  
Ellis Hoffland ◽  
Anna Rosling ◽  
...  
Keyword(s):  
Molecular Identification ◽  
Sequence Similarity ◽  
Mineral Soil ◽  
Molecular Techniques ◽  
Root Tip ◽  
Root Tips ◽  
Soil Horizons ◽  
Novel Approach ◽  
Total Dna ◽  
Identification Techniques

ABSTRACT Molecular identification techniques based on total DNA extraction provide a unique tool for identification of mycelium in soil. Using molecular identification techniques, the ectomycorrhizal (EM) fungal community under coniferous vegetation was analyzed. Soil samples were taken at different depths from four horizons of a podzol profile. A basidiomycete-specific primer pair (ITS1F-ITS4B) was used to amplify fungal internal transcribed spacer (ITS) sequences from total DNA extracts of the soil horizons. Amplified basidiomycete DNA was cloned and sequenced, and a selection of the obtained clones was analyzed phylogenetically. Based on sequence similarity, the fungal clone sequences were sorted into 25 different fungal groups, or operational taxonomic units (OTUs). Out of 25 basidiomycete OTUs, 7 OTUs showed high nucleotide homology (≥99%) with known EM fungal sequences and 16 were found exclusively in the mineral soil. The taxonomic positions of six OTUs remained unclear. OTU sequences were compared to sequences from morphotyped EM root tips collected from the same sites. Of the 25 OTUs, 10 OTUs had ≥98% sequence similarity with these EM root tip sequences. The present study demonstrates the use of molecular techniques to identify EM hyphae in various soil types. This approach differs from the conventional method of EM root tip identification and provides a novel approach to examine EM fungal communities in soil.

A missing link: a distributed cognitive perspective on fit

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Gayanga Bandara Herath
Keyword(s):  
Design Methodology ◽  
Social Systems ◽  
Cognitive Perspective ◽  
Missing Link ◽  
Content Type ◽  
Narrow Focus ◽  
Cognitive Framework ◽  
Novel Approach ◽  
Complex Social Systems

PurposeThis article presents a cognitive framework to study dynamic/adaptive aspects of a collection of popular fit measures used in organisation research, in an attempt to highlight what there is to be gained.Design/methodology/approachThis paper uses a distributed e-cognition (DEC) framework to examine the current organisational literature of fit measures.FindingsThis paper highlights that most measures have a rather narrow focus and do not address dynamic/adaptive aspects in complex social systems (e.g. organisations). To both provide a way to integrate fit measures and cover the cognition gap in this literature, this article highlights the need for a more sophisticated measure.Originality/valueThis paper provides a novel approach to examining organisational fit literature through a distributed (e)-cognitive framework.

Reconstructing Phylogenetic Relationships Based on Repeat Sequence Similarities

2019 ◽  
Author(s):  
Daniel Vitales ◽  
Sònia Garcia ◽  
Steven Dodsworth
Keyword(s):  
Phylogenetic Relationships ◽  
Sequence Similarity ◽  
Information Source ◽  
Repeat Sequence ◽  
Combined Application ◽  
Novel Approach ◽  
Genome Wide ◽  
History Of ◽  
Sequence Similarities ◽  
Phylogenetic Method

AbstractA recent phylogenetic method based on genome-wide abundance of different repeat types proved to be useful in reconstructing the evolutionary history of several plant and animal groups. Here, we demonstrate that an alternative information source from the repeatome can also be employed to infer phylogenetic relationships among taxa. Specifically, this novel approach makes use of the repeat sequence similarity matrices obtained from the comparative clustering analyses of RepeatExplorer 2, which are subsequently transformed to between-taxa distance matrices. These pairwise matrices are used to construct neighbour-joining trees for each of the top most-abundant clusters and they are finally summarized in a consensus network. This methodology was tested on three groups of angiosperms and one group of insects, resulting in congruent evolutionary hypotheses compared to more standard systematic analyses based on commonly used DNA markers. We propose that the combined application of these phylogenetic approaches based on repeat abundances and repeat sequence similarities could be helpful to understand mechanisms governing genome and repeatome evolution.

KSTR: Keyword-Aware Skyline Travel Route Recommendation

2015 ◽  
Author(s):  
Yu-Ting Wen ◽  
Kae-Jer Cho ◽  
Wen-Chih Peng ◽  
Jinyoung Yeo ◽  
Seung-won Hwang
Keyword(s):  
Route Recommendation ◽  
Travel Route Recommendation
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