scholarly journals A Link Prediction Strategy for Personalized Tweet Recommendation through Doc2Vec Approach

2017 ◽  
Vol 2 (4) ◽  
pp. 63 ◽  
Author(s):  
Mojtaba Zahedi Amiri ◽  
Abdullah Shobi

<p><em>Nowadays with growth of using Internet as a principle way of communication, likes different social medias channels (Twitter,</em><em> </em><em>Facebook,</em><em> </em><em>etc</em><em>.</em><em>) and also access to huge amount of information like News, there appear a main research subject to help users to find his/her interests among vast amount of relevant and irrelevant information. Recommender systems are helped to handle information overload problem and in this paper we introduce our Tweet Recommendation System that implement user</em><em>’</em><em>s Twitter information (Tweets, Retweet, Like,...) as a source of user’s information. In this work the semantic of tweets that regard as a User’s Explicit Interests</em><em> </em><em>(e.g.</em><em>,</em><em> person, events, product mentioned in user’s tweets) are identified with the Doc2vec approach and recommend similar tweets through link-prediction strategy. The experiment results show that Doc2Vec approach is a</em><em> </em><em>better approach than the other previous approaches.</em></p>

2020 ◽  
Vol 10 (21) ◽  
pp. 7748
Author(s):  
Zeshan Fayyaz ◽  
Mahsa Ebrahimian ◽  
Dina Nawara ◽  
Ahmed Ibrahim ◽  
Rasha Kashef

Recommender systems are widely used to provide users with recommendations based on their preferences. With the ever-growing volume of information online, recommender systems have been a useful tool to overcome information overload. The utilization of recommender systems cannot be overstated, given its potential influence to ameliorate many over-choice challenges. There are many types of recommendation systems with different methodologies and concepts. Various applications have adopted recommendation systems, including e-commerce, healthcare, transportation, agriculture, and media. This paper provides the current landscape of recommender systems research and identifies directions in the field in various applications. This article provides an overview of the current state of the art in recommendation systems, their types, challenges, limitations, and business adoptions. To assess the quality of a recommendation system, qualitative evaluation metrics are discussed in the paper.


2012 ◽  
Vol 267 ◽  
pp. 87-90
Author(s):  
Pu Wang

E-commerce recommendation system is one of the most important and the most successful application field of information intelligent technology. Recommender systems help to overcome the problem of information overload on the Internet by providing personalized recommendations to the customers. Recommendation algorithm is the core of the recommendation system. Collaborative filtering recommendation algorithm is the personalized recommendation algorithm that is used widely in e-commerce recommendation system. Collaborative filtering has been a comprehensive approach in recommendation system. But data are always sparse. This becomes the bottleneck of collaborative filtering. Collaborative filtering is regarded as one of the most successful recommender systems within the last decade, which predicts unknown ratings by analyzing the known ratings. In this paper, an electronic commerce collaborative filtering recommendation algorithm based on product clustering is given. In this approach, the clustering of product is used to search the recommendation neighbors in the clustering centers.


2021 ◽  
pp. 1-13
Author(s):  
Jenish Dhanani ◽  
Rupa Mehta ◽  
Dipti Rana

Legal practitioners analyze relevant previous judgments to prepare favorable and advantageous arguments for an ongoing case. In Legal domain, recommender systems (RS) effectively identify and recommend referentially and/or semantically relevant judgments. Due to the availability of enormous amounts of judgments, RS needs to compute pairwise similarity scores for all unique judgment pairs in advance, aiming to minimize the recommendation response time. This practice introduces the scalability issue as the number of pairs to be computed increases quadratically with the number of judgments i.e., O (n2). However, there is a limited number of pairs consisting of strong relevance among the judgments. Therefore, it is insignificant to compute similarities for pairs consisting of trivial relevance between judgments. To address the scalability issue, this research proposes a graph clustering based novel Legal Document Recommendation System (LDRS) that forms clusters of referentially similar judgments and within those clusters find semantically relevant judgments. Hence, pairwise similarity scores are computed for each cluster to restrict search space within-cluster only instead of the entire corpus. Thus, the proposed LDRS severely reduces the number of similarity computations that enable large numbers of judgments to be handled. It exploits a highly scalable Louvain approach to cluster judgment citation network, and Doc2Vec to capture the semantic relevance among judgments within a cluster. The efficacy and efficiency of the proposed LDRS are evaluated and analyzed using the large real-life judgments of the Supreme Court of India. The experimental results demonstrate the encouraging performance of proposed LDRS in terms of Accuracy, F1-Scores, MCC Scores, and computational complexity, which validates the applicability for scalable recommender systems.


Author(s):  
Aya Taleb ◽  
Rizik M. H. Al-Sayyed ◽  
Hamed S. Al-Bdour

In this research, a new technique to improve the accuracy of the link prediction for most of the networks is proposed; it is based on the prediction ensemble approach using the voting merging technique. The new proposed ensemble called Jaccard, Katz, and Random models Wrapper (JKRW), it scales up the prediction accuracy and provides better predictions for different sizes of populations including small, medium, and large data. The proposed model has been tested and evaluated based on the area under curve (AUC) and accuracy (ACC) measures. These measures applied to the other models used in this study that has been built based on the Jaccard Coefficient, Katz, Adamic/Adar, and Preferential attachment. Results from applying the evaluation matrices verify the improvement of JKRW effectiveness and stability in comparison to the other tested models.  The results from applying the Wilcoxon signed-rank method (one of the non-parametric paired tests) indicate that JKRW has significant differences compared to the other models in the different populations at <strong>0.95</strong> confident interval.


Virittäjä ◽  
2017 ◽  
Vol 121 (2) ◽  
Author(s):  
Krista Ojutkangas

Tutkimuksen tavoitteena on selvittää, millaisissa konstruktioissa suomen seuralaisuutta ilmaisevat mukana ja mukaan esiintyvät. Seuralaisuussuhteelle on tyypillistä, että suhteen osallistujat tai vähintään kiintopiste ovat ihmisiä ja että osallistujien välillä on symmetriaero: seuralainen (engl. companion) osallistuu tilanteeseen epäsuorasti, seurattavan (engl. accompanee) välityksellä. Suomen grammeille ominaiseen tapaan mukana- ja mukaan-sanoja käytetään syntaktisesti monenlaisissa asemissa siten, että kiintopisteen (seurattavan) ilmaisun tyyppi vaihtelee. Tutkimuksessa selvitetäänkin, mikä on kiintopisteen ilmaisutavan rooli siinä, miten seuralaisuussuhteen osallistujien välinen epäsymmetria hahmottuu. Tutkimuksen syntaktisessa luokittelussa pidetään lähtökohtana postpositiokonstruktiota, jossa osallistujien välisen symmetriaeron voi katsoa perustuvan kiintopisteen viitepisteroolin kautta grammin semantiikkaan (tyyppi lapio oli kaivajan mukana). Symmetriaero sen sijaan voimistuu, kun kiintopiste edustuu omistusliitteen välityksellä subjektina (tyyppi hän otti lapion mukaansa) tai kun se ilmaistaan teemapaikalla paikallissijaisena adverbiaalina (tyyppi hänellä oli lapio mukana[an]). Symmetriaero sen sijaan heikkenee, jos (toissijainen) kiintopiste ilmaistaan adverbiaalina muualla kuin teemapaikalla (tyyppi hän oli mukana kaivamassa), ja vetäytyy taustatiedoksi, kun kiintopistettä ei ilmaista lainkaan (tyyppi hän on mukana). Tutkimus perustuu aineistoon, jossa ovat edustettuina 1800-luvun kirjakieli, Lauseopin arkiston murrehaastattelut ja nykykirjakieli. Aineisto osoittaa, että mukana- ja mukaan-grammeilla ilmaistuissa seuralaisuussuhteissa on tapahtunut muutos: 1800-luvun kirjakielen ja pääosin 1960-luvulla tallennetun murreaineiston esiintymissä yleisin kiintopiste on ihminen, kun taas nykykirjakielen aineistossa kiintopisteeksi hahmottuu tyypillisimmin toiminta. Kiintopisteen semanttinen tyyppi ja sen kielellinen ilmaisukeino ovat suorassa suhteessa toisiinsa. Ihmiskiintopiste ilmaistaan yleisimmin subjektin kanssa samaviitteisellä omistusliitteellä tai teemapaikkaisella paikallissijaisella elementillä ja toimintakiintopiste puolestaan ei-teemapaikkaisella paikallissijaisella elementillä. Eri ilmaisukeinot jakautuvat eri verbien ympärille rakentuvien konstruktioiden kesken. Tutkimuksen perusteella voi todeta, että esiintymäkonstruktiolla on merkittävä rooli siinä, millaista seuralaisuutta mukana- tai mukaan-grammilla kuvataan.   Finnish mukana and mukaan ‘with, along’ as comitative markers: Grammatical roles of expressions of the landmarks, constructions, and asymmetry between the participants of the accompaniment relation The topic of this article is the syntax of Finnish comitative markers mukana and mukaan ’with, along’. Comitative markers express accompaniment relations, which are typically conceived as being asymmetrical: the accompanee (landmark) is the pre-dominant participant, while the companion (trajector) is involved in the situation only via the accompanee (see Stolz et al. 2006: 26–27). However, markers such as mukana and mukaan are used in several syntactic constructions where the grammatical roles of expressions of the accompanees/landmarks vary. The main research question of the article is, how does the grammatical role of expression of the accompanee/landmark affect the asymmetry between the participants of the accompaniment relation. Five syntactic construction types were analysed from a corpus data. On the basis of this study, it is shown that syntactic variation has an effect on the conceived asymmetry between the accompanee and the companion, and that syntax makes an important contribution to the semantics of comitative constructions. In strongly asymmetric accompaniment relations, a human accompanee is expressed by a possessive suffix affixed to the comitative marker, or by a clause-initial adverbial. On the other hand, the question of asymmetry contracts to the background when the accompanee is expressed by a non-clause-initial adverbial and when the accompanee is implicit, without any overt marking. The research is based on a corpus data comprising 19th-century written Finnish, dialect interviews, and modern written Finnish. The data shows that accompaniment relations expressed by mukana and mukaan have changed: in the 19th-century and dialect data, the majority of the landmarks are humans, but in the modern data activities dominate as (secondary) landmarks.  


Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Chaohua Fang ◽  
Qiuyun Lu

With the rapid development of information technology and data science, as well as the innovative concept of “Internet+” education, personalized e-learning has received widespread attention in school education and family education. The development of education informatization has led to a rapid increase in the number of online learning users and an explosion in the number of learning resources, which makes learners face the dilemma of “information overload” and “learning lost” in the learning process. In the personalized learning resource recommendation system, the most critical thing is the construction of the learner model. Currently, most learner models generally have a lack of scientific focus that they have a single method of obtaining dimensions, feature attributes, and low computational complexity. These problems may lead to disagreement between the learner’s learning ability and the difficulty of the recommended learning resources and may lead to the cognitive overload or disorientation of learners in the learning process. The purpose of this paper is to construct a learner model to support the above problems and to strongly support individual learning resources recommendation by learning the resource model which effectively reduces the problem of cold start and sparsity in the recommended process. In this paper, we analyze the behavioral data of learners in the learning process and extract three features of learner’s cognitive ability, knowledge level, and preference for learning of learner model analysis. Among them, the preference model of the learner is constructed using the ontology, and the semantic relation between the knowledge is better understood, and the interest of the student learning is discovered.


Author(s):  
V. P. Terin

In contradistinction to the book and the other typographic products, the electronic media operates on a 24-hour-a-day basis evoking simultaneity as the guiding mode of perception and thinking for all those under its influence. The discovery of this fact manifested itself in the formation and development of the managerial technologies operating by means of the electronic information environment and following the principle of simultaneity in the first place. Thus, at the end of the 1960s already the election campaigns in the U.S.A. began to operate on the basis of the final cause as the guiding principle of the country's mass consciousness motivating to carry out each particular event as if already rejoicing at the victory. With this in mind, there emerged a problem of applying this approach with its enormous managerial potential elsewhere. To add, simultaneity as a norm of perception and thinking turned out to be increasingly important with the advent of the electrical telegraph and the press relying on its short disconnected messages instantaneously arriving from all parts of the world. All the other media, which emerged in the wake of this development, has served to fortify this mode of thought as governing in the electronic information environment. The potential of the electronically operating global managerial technologies is quickly growing. The article also deals with the information overload and pattern recognition problem understood in managerial terms as well as mythologization and demythologization processes as they are necessitated by the electronic media coverage worldwide.


2021 ◽  
Vol 2 (2) ◽  
pp. 66-80
Author(s):  
Meng-Kuan Chen ◽  
Hsin-Wen Wei ◽  
Wei-Tsong Lee

Recommender systems have been applied on a variety of applications including movies, music, news, books, research articles, search queries, and travel information. Instead of searching travel information from the extremely huge amount of travel data, a personalized travel recommender system is desired. However, an inappropriate travel recommendation may result from a wrong season, even if it is already a correct location. The current recommender systems from time to time make an inappropriate commendation without considering the seasonal factor. In order to resolve the discrepancy, the seasonal factor should have been taken into consideration when making a good travel recommender system. Therefore, this study has taken the trend analysis, time series, and seasonal factor into considerations to cope with the above mentioned discrepancy and to make the travel recommender system renders a better fit.


2021 ◽  
Vol 7 (6) ◽  
pp. 5440-5452
Author(s):  
Song Shan ◽  
Min Chunfang

Objectives: In Tianzhu dialect, the use of the future aspect marker "Dai[tɛi44]" is frequent. The grammatical meaning of the future aspect marker, "verb phrase (VP) +'Dai[tɛi44]+[lio21]'", in Tianzhu dialect can be divided into two categories according to the differences of VP: one indicates that the end of the action is about to be reached, that is, "VP +'Dai1[tɛi44]+[lio21]'"; the other indicates that the action is about to begin, that is, "VP +‘Dai2[tɛi44]+[lio21]’ ". This article takes the Tianzhu dialect aspect marker "Dai[tɛi44]" as the main research object, and focuses on the grammatical functions and semantic features of "Dai1[tɛi44]" and "Dai2[tɛi44]" by studying the actionality types of verbs in Tianzhu dialect, and compares the future aspect marker "Dai[tɛi44]" in Tianzhu dialect with the future aspect markers of other Chinese dialect in Northwest China, and generalizes the geographical distribution and regional characteristics of the future aspect marker "Dai[tɛi44]".


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