This document summarizes and discusses several papers related to topic modeling and recommendation systems using bipartite graphs. It discusses Topic-Sensitive PageRank, which uses personalization vectors to determine page importance for specific topics. It also discusses using random walks on bipartite graphs to measure relatedness between nodes and extract topics. Methods discussed include label propagation for community detection, network projection for recommendation, and inductive model generation for text classification using a heterogeneous bipartite network. Matrix factorization techniques for recommendation are also covered, including their advantages over other methods.
An Attempt to Automate the Process of Source EvaluationIDES Editor
Credibility of a web-based document is an
important concern, when a large number of documents is
available on internet for a given subject. In this paper, various
criteria that affect the credibility of a document are explored.
An attempt is made to automate the process of assigning a
credibility score to a web-based document. Presently the
prototype of the tool developed is restricted to only four criteria
– type of website, date of update, sentiment analysis and a
pre-defined Google page rank. Also a separate module for
checking “link integrity” of a website is developed. To obtain
empirical validity of the tool, a pilot study is conducted which
collects credibility scoring for a set of websites by human
judges. The correlation between the scores given by human
judges and the scores obtained by the tool developed is low.
The possible reasons for the low correlation are firstly, the
tool is restricted to only four criteria, and secondly, subjects
themselves had no agreement. Apparently they judged the
website on different criteria, and not weighted overall. Further
enhancements to the work done in this paper can be of great
use to a novice user, who wishes to search a reliable webbased
document on any specific topic. This can be done by
including all criteria (discussed in this paper) for calculating
the credibility score of a website.
An overview of CapitalRoad's programs and approach to building a strong ecosystem of investors, sponsors, and entrepreneurs targeting the growth of early stage Canadian technology companies.
An Attempt to Automate the Process of Source EvaluationIDES Editor
Credibility of a web-based document is an
important concern, when a large number of documents is
available on internet for a given subject. In this paper, various
criteria that affect the credibility of a document are explored.
An attempt is made to automate the process of assigning a
credibility score to a web-based document. Presently the
prototype of the tool developed is restricted to only four criteria
– type of website, date of update, sentiment analysis and a
pre-defined Google page rank. Also a separate module for
checking “link integrity” of a website is developed. To obtain
empirical validity of the tool, a pilot study is conducted which
collects credibility scoring for a set of websites by human
judges. The correlation between the scores given by human
judges and the scores obtained by the tool developed is low.
The possible reasons for the low correlation are firstly, the
tool is restricted to only four criteria, and secondly, subjects
themselves had no agreement. Apparently they judged the
website on different criteria, and not weighted overall. Further
enhancements to the work done in this paper can be of great
use to a novice user, who wishes to search a reliable webbased
document on any specific topic. This can be done by
including all criteria (discussed in this paper) for calculating
the credibility score of a website.
An overview of CapitalRoad's programs and approach to building a strong ecosystem of investors, sponsors, and entrepreneurs targeting the growth of early stage Canadian technology companies.
Highlights:
Annual inflation stands positive
Manufacturing growth has become stronger
Government debt servicing costs have been reduced
"In Focus":
What are the different effects of oil price developments on Latvia's inflation? autori: Oļegs Tkčevs and Andrejs Bessonovs
Tonya shirelle | Life Coaching And Personal Coachingtonyashirelle
Life coaching can be effective in many situations, for example in helping a person's career direction and development, or for personal fulfillment or life change more generally.
A training powerpoint presentation for employees in patient confidentiality as a follow up on multiple breaches of confidentiality and privacy of protected health information of celebrities in a hospital setting.
Wattle Grove Primary School - Class Parent Information Evening 2016Stuart Meachem
Parents attending class information meetings to meet the staff and learn about the processes and procedures in the class, as well as have any questions answered...
"Как вырастить ответственность сотрудников - Что надо написать в инструкцию, ...awgua
Как вырастить ответственность сотрудников - Что надо написать в инструкцию, чтобы сотрудник не перекидывал на других свою ответственность.
- Как мотивировать персонал на написание инструкций самостоятельно
- Как сделать инструкцию постоянным рабочим инструментом для повышения эффективности сотрудников
- Что должно быть в инструкции, чтобы в компании было меньше "пожаров" и потерь
- Как должностными инструкциями обезопасить себя от плохих "незаменимых" сотрудников.
Александр Варламов, президент представительства "BusinessForward" в Украине.
Incremental Page Rank Computation on Evolving Graphs : NOTESSubhajit Sahu
Highlighted notes while doing research work under Prof. Dip Sankar Banerjee and Prof. Kishore Kothapalli:
Incremental Page Rank Computation on Evolving Graphs.
https://dl.acm.org/doi/10.1145/1062745.1062885
This paper describes a simple method for computing dynamic pagerank, based on the fact that change of out-degree of a node does not affect its pagerank (first order markov property). The part of graph which is updated (edge additions / edge deletions / weight changes) is used to find the affected partition of graph using BFS. The unaffected partition is simply scaled, and pagerank computation is done only for the affected partition.
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
We are good IEEE java projects development center in Chennai and Pondicherry. We guided advanced java technologies projects of cloud computing, data mining, Secure Computing, Networking, Parallel & Distributed Systems, Mobile Computing and Service Computing (Web Service).
For More Details:
http://jpinfotech.org/final-year-ieee-projects/2014-ieee-projects/java-projects/
Highlights:
Annual inflation stands positive
Manufacturing growth has become stronger
Government debt servicing costs have been reduced
"In Focus":
What are the different effects of oil price developments on Latvia's inflation? autori: Oļegs Tkčevs and Andrejs Bessonovs
Tonya shirelle | Life Coaching And Personal Coachingtonyashirelle
Life coaching can be effective in many situations, for example in helping a person's career direction and development, or for personal fulfillment or life change more generally.
A training powerpoint presentation for employees in patient confidentiality as a follow up on multiple breaches of confidentiality and privacy of protected health information of celebrities in a hospital setting.
Wattle Grove Primary School - Class Parent Information Evening 2016Stuart Meachem
Parents attending class information meetings to meet the staff and learn about the processes and procedures in the class, as well as have any questions answered...
"Как вырастить ответственность сотрудников - Что надо написать в инструкцию, ...awgua
Как вырастить ответственность сотрудников - Что надо написать в инструкцию, чтобы сотрудник не перекидывал на других свою ответственность.
- Как мотивировать персонал на написание инструкций самостоятельно
- Как сделать инструкцию постоянным рабочим инструментом для повышения эффективности сотрудников
- Что должно быть в инструкции, чтобы в компании было меньше "пожаров" и потерь
- Как должностными инструкциями обезопасить себя от плохих "незаменимых" сотрудников.
Александр Варламов, президент представительства "BusinessForward" в Украине.
Incremental Page Rank Computation on Evolving Graphs : NOTESSubhajit Sahu
Highlighted notes while doing research work under Prof. Dip Sankar Banerjee and Prof. Kishore Kothapalli:
Incremental Page Rank Computation on Evolving Graphs.
https://dl.acm.org/doi/10.1145/1062745.1062885
This paper describes a simple method for computing dynamic pagerank, based on the fact that change of out-degree of a node does not affect its pagerank (first order markov property). The part of graph which is updated (edge additions / edge deletions / weight changes) is used to find the affected partition of graph using BFS. The unaffected partition is simply scaled, and pagerank computation is done only for the affected partition.
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
To Get any Project for CSE, IT ECE, EEE Contact Me @ 09666155510, 09849539085 or mail us - ieeefinalsemprojects@gmail.com-Visit Our Website: www.finalyearprojects.org
We are good IEEE java projects development center in Chennai and Pondicherry. We guided advanced java technologies projects of cloud computing, data mining, Secure Computing, Networking, Parallel & Distributed Systems, Mobile Computing and Service Computing (Web Service).
For More Details:
http://jpinfotech.org/final-year-ieee-projects/2014-ieee-projects/java-projects/
SEMANTICS GRAPH MINING FOR TOPIC DISCOVERY AND WORD ASSOCIATIONSIJDKP
Big Data creates many challenges for data mining experts, in particular in getting meanings of text data. It is beneficial for text mining to build a bridge between word embedding process and graph capacity to connect the dots and represent complex correlations between entities. In this study we examine processes of building a semantic graph model to determine word associations and discover document topics. We introduce a novel Word2Vec2Graph model that is built on top of Word2Vec word embedding model. We demonstrate how this model can be used to analyze long documents, get unexpected word associations and uncover document topics. To validate topic discovery method we transfer words to vectors and vectors to images and use CNN deep learning image classification.
Data Mining Module 5 Business Analytics.pdfJayanti Pande
Business Analytics Paper 2
| Data Mining | RTMNU Nagpur University MBA | Module 5
| Web Mining and Text Mining | By Jayanti Pande | ProNotesJRP | JRP Notes
A Generalization of the PageRank Algorithm : NOTESSubhajit Sahu
This paper discusses a method of Generalizing PageRank algorithm for different types of networks. Rank of each vertex is considered to be dependent upon both the in- and out-edges. Each edge can also have differing importance. This solves the problem of dead ends and spider traps without the need of taxation (?).
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Abstract— PageRank is a well-known algorithm that has been used to understand the structure of the Web. In its classical formulation the algorithm considers only forward looking paths in its analysis- a typical web scenario. We propose a generalization of the PageRank algorithm based on both out-links and in-links. This generalization enables the elimination network anomalies- and increases the applicability of the algorithm to an array of new applications in networked data. Through experimental results we illustrate that the proposed generalized PageRank minimizes the effect of network anomalies, and results in more realistic representation of the network.
Keywords- Search Engine; PageRank; Web Structure; Web Mining; Spider-Trap; dead-end; Taxation;Web spamming
Keyword search is an intuitive paradigm for searching linked data sources on the web. We propose to route keywords only to relevant sources to reduce the high cost of processing keyword search queries over all sources.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
Machine Status Prediction for Dynamic and Heterogenous Cloud Environmentjins0618
The widespread utilization of cloud computing services
has brought in the emergence of cloud service reliability
as an important issue for both cloud providers and users. To
enhance cloud service reliability and reduce the subsequent losses, the future status of virtual machines should be monitored in real time and predicted before they crash. However, most existing methods ignore the following two characteristics of actual cloud
environment, and will result in bad performance of status prediction:
1. cloud environment is dynamically changing; 2. cloud
environment consists of many heterogeneous physical and virtual
machines. In this paper, we investigate the predictive power of
collected data from cloud environment, and propose a simple yet
general machine learning model StaP to predict multiple machine
status. We introduce the motivation, the model development
and optimization of the proposed StaP. The experimental results
validated the effectiveness of the proposed StaP.
Latent Interest and Topic Mining on User-item Bipartite Networksjins0618
Latent Factor Model (LFM) is extensively used in
dealing with user-item bipartite networks in service recommendation systems. To alleviate the limitations of LFM, this papers presents a novel unsupervised learning model, Latent Interest and Topic Mining model (LITM), to automatically
mine the latent user interests and item topics from user-item
bipartite networks. In particular, we introduce the motivation
and objectives of this bipartite network based approach, and
detail the model development and optimization process of the
proposed LITM. This work not only provides an efficient method for latent user interest and item topic mining, but also highlights a new way to improve the accuracy of service recommendation. Experimental studies are performed and the results validate the LITM’s efficiency in model training, and its ability to provide better service recommendation performance based on user-item bipartite networks are demonstrated.
Web Service QoS Prediction Approach in Mobile Internet Environmentsjins0618
Existing many Web service QoS prediction
approaches are very accurate in Internet environments,
however they cannot provide accurate prediction values in
Mobile Internet environments since QoS values of Web
services have great volatility. In this paper, we propose an
accurate Web service QoS prediction approach by weakening
the volatility of QoS data from Web services in Mobile Internet
environments. This approach contains three process, i.e., QoS
preprocessing, user similarity computing, and QoS predicting.
We have implemented our proposed approach with experiment
based on real world and synthetic datasets. The results show
that our approach outperforms other approaches in Mobile
Internet environments.
Opendatabay - Open Data Marketplace.pptxOpendatabay
Opendatabay.com unlocks the power of data for everyone. Open Data Marketplace fosters a collaborative hub for data enthusiasts to explore, share, and contribute to a vast collection of datasets.
First ever open hub for data enthusiasts to collaborate and innovate. A platform to explore, share, and contribute to a vast collection of datasets. Through robust quality control and innovative technologies like blockchain verification, opendatabay ensures the authenticity and reliability of datasets, empowering users to make data-driven decisions with confidence. Leverage cutting-edge AI technologies to enhance the data exploration, analysis, and discovery experience.
From intelligent search and recommendations to automated data productisation and quotation, Opendatabay AI-driven features streamline the data workflow. Finding the data you need shouldn't be a complex. Opendatabay simplifies the data acquisition process with an intuitive interface and robust search tools. Effortlessly explore, discover, and access the data you need, allowing you to focus on extracting valuable insights. Opendatabay breaks new ground with a dedicated, AI-generated, synthetic datasets.
Leverage these privacy-preserving datasets for training and testing AI models without compromising sensitive information. Opendatabay prioritizes transparency by providing detailed metadata, provenance information, and usage guidelines for each dataset, ensuring users have a comprehensive understanding of the data they're working with. By leveraging a powerful combination of distributed ledger technology and rigorous third-party audits Opendatabay ensures the authenticity and reliability of every dataset. Security is at the core of Opendatabay. Marketplace implements stringent security measures, including encryption, access controls, and regular vulnerability assessments, to safeguard your data and protect your privacy.
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
As Europe's leading economic powerhouse and the fourth-largest hashtag#economy globally, Germany stands at the forefront of innovation and industrial might. Renowned for its precision engineering and high-tech sectors, Germany's economic structure is heavily supported by a robust service industry, accounting for approximately 68% of its GDP. This economic clout and strategic geopolitical stance position Germany as a focal point in the global cyber threat landscape.
In the face of escalating global tensions, particularly those emanating from geopolitical disputes with nations like hashtag#Russia and hashtag#China, hashtag#Germany has witnessed a significant uptick in targeted cyber operations. Our analysis indicates a marked increase in hashtag#cyberattack sophistication aimed at critical infrastructure and key industrial sectors. These attacks range from ransomware campaigns to hashtag#AdvancedPersistentThreats (hashtag#APTs), threatening national security and business integrity.
🔑 Key findings include:
🔍 Increased frequency and complexity of cyber threats.
🔍 Escalation of state-sponsored and criminally motivated cyber operations.
🔍 Active dark web exchanges of malicious tools and tactics.
Our comprehensive report delves into these challenges, using a blend of open-source and proprietary data collection techniques. By monitoring activity on critical networks and analyzing attack patterns, our team provides a detailed overview of the threats facing German entities.
This report aims to equip stakeholders across public and private sectors with the knowledge to enhance their defensive strategies, reduce exposure to cyber risks, and reinforce Germany's resilience against cyber threats.
Techniques to optimize the pagerank algorithm usually fall in two categories. One is to try reducing the work per iteration, and the other is to try reducing the number of iterations. These goals are often at odds with one another. Skipping computation on vertices which have already converged has the potential to save iteration time. Skipping in-identical vertices, with the same in-links, helps reduce duplicate computations and thus could help reduce iteration time. Road networks often have chains which can be short-circuited before pagerank computation to improve performance. Final ranks of chain nodes can be easily calculated. This could reduce both the iteration time, and the number of iterations. If a graph has no dangling nodes, pagerank of each strongly connected component can be computed in topological order. This could help reduce the iteration time, no. of iterations, and also enable multi-iteration concurrency in pagerank computation. The combination of all of the above methods is the STICD algorithm. [sticd] For dynamic graphs, unchanged components whose ranks are unaffected can be skipped altogether.