The Dynamics of Multi-Modal Networks

The widespread study of networks in diverse domains, including social, technological, and scientific settings, has increased the interest in statistical and machine learning techniques for network analysis. Many of these networks are complex, involving more than one kind of entity, and multiple relationship types, both changing over time. While there have been many network analysis methods proposed for problems such as network evolution, community detection, information diffusion and opinion leader identification, the majority of these methods assume a single entity type, a single edge type and often no temporal dynamics. One of the main shortcomings of these traditional techniques is their inadequacy for capturing higher-order dependencies often present in real, complex networks. To address these shortcomings, I focus on analysis and inference in dynamic, multi-modal, multi-relational networks, containing multiple entity types (such as people, social groups, organizations, locations, etc.), and different relationship types (such as friendship, membership, affiliation, etc.). An example from social network theory is a network describing users, organizations and interest groups, where users have different types of ties among each other, such as friendship, family ties, etc., as well as affiliation and membership links with organizations and interest groups. By considering the complex structure of these networks rather than limiting the analysis to a single entity or relationship type, I show how we can build richer predictive models that provide better understanding of the network dynamics, and thus result in better quality predictions. In the first part of my dissertation, I address the problems of network evolution and clustering. For network evolution, I describe methods for modeling the interactions between different modalities, and propose a co-evolution model for social and affiliation networks. I then move to the problem of network clustering, where I propose a novel algorithm for clustering multi-modal, multi-relational data. The second part of my dissertation focuses on the temporal dynamics of interactions in complex networks, from both user-level and network-level perspectives. For the user-centric approach, I analyze the dynamics of user relationships with other entity types, proposing a measure of the "loyalty" a user shows for a given group or topic, based on her temporal interaction pattern. I then move to macroscopic-level approaches for analyzing the dynamic processes that occur on a network scale. I propose a new differential adaptive diffusion model for incorporating diversity and trust in the process of information diffusion on multi-modal, multi-relational networks. I also discuss the implications of the proposed diffusion model on designing new strategies for viral marketing and influential detection. I validate all the proposed methods on several real-world networks from multiple domains

THE TYPOLOGY OF REGIONAL MERGERS FROM THE PERSPECTIVE OF FINANCIAL-ACCOUNTING ASPECTS

The interest for approaching this paper is determined by the actuality of the theme concerning mergers, and also by the scale proportions this type of transactions have arrived at, both at global level and also at national level, everything having as cornerstone a market economy within which competitiveness plays a more and more important role. The aim of the study consists in analyzing the external restructuring of entities under the form of mergers. On one side, in order to clarify and deepen the theoretical aspects concerning mergers, and on the other side, in order to identify certain features related to merger transactions in Cluj County. The aim of the study is to identify the conditions and manner of merger development within commercial entities from Cluj County and to establish a typology relying on the results concerning the relationship between the entities' shareholding structure, their contribution and the exchange ratio when performing the transactions. The actuality of the theme, the requirement and the increasing manifestation of the merger phenomenon also within the Romanian teritory, the necessity of a thorough analysis of merger trends and typologies, they all have been trigger factors of this objective. In order to achieve the objective a research methodology was followed, assumptions were made, which have been confirmed of infirmed. The methodological sphere consists of an approach of considered quantitative and qualitative models, of techniques for data collection, hypotheses testing, but also of research boundaries. As a result of the processing and analysis of the data on which this study relies, one arrived to the following conclusions concerning mergers that were performed in Cluj County, conclusions which could lead to the elaboration of a typology for the mergers that have occurred in this region: in terms of shareholding structure, the two entities usually had a joint majority shareholder, and regarding the financial aspects, the contributions of both entities are in most of the cases positive, and the contribution of the absorbent entity is greater, and rarely, when the contributions are negative, these contributions usually belong to the absorbed entity. Also, when the shareholding structure is the same, the exchange ratio is usually 1:1.merger, contribution, exchange ratio, positive equity, negative equity

Pengembangan Sistem Informasi Pencatatan dan Pelaporan Akupunktur di Poliklinik Akupunktur Rumah Sakit PKU Delanggu

The Policlinic Acupuncture PKU Muhammadiyah Delanggu Hospital needs the system of recording and reporting data properly and accurately. Up to how the recording and processing of data activities run less than optimal, because there are still done manually, where the other policlinic have done the system of information, so when the officer arrange reporting, theyhae difficulties because they must record and look for the data before that will be need. The purposing this research is to do the development of system, with a draft system for recording and reporting of data on the Policlinic Acupuncture PKU Muhammadiyah Delanggu Hospital. This type of research is developing and researching with qualitative approach and system development. The development system method which used prototypemethod. This research sample consists of 2 acupuncture terapist, 1 medical record officer of out patient, and 1 Kasubag Kepegawaian (receiver reports officer).Results of user identification, researchers designed the 5 data flow diagram (DFD) is a diagram cortex recording and reporting information system of acupuncture, processing DFD data base recording and reporting of acupuncture, DFD recording patient data, DFD therapy techniques, DFD summary report the number of patients, entity relationship diagram (ERD), 15 table data base and 17 input system interface design: 16 and outputs: 1 (Summary Report Number of Patients). The developing system use PHP and MySQL data base

Generating Preview Tables for Entity Graphs

Users are tapping into massive, heterogeneous entity graphs for many applications. It is challenging to select entity graphs for a particular need, given abundant datasets from many sources and the oftentimes scarce information for them. We propose methods to produce preview tables for compact presentation of important entity types and relationships in entity graphs. The preview tables assist users in attaining a quick and rough preview of the data. They can be shown in a limited display space for a user to browse and explore, before she decides to spend time and resources to fetch and investigate the complete dataset. We formulate several optimization problems that look for previews with the highest scores according to intuitive goodness measures, under various constraints on preview size and distance between preview tables. The optimization problem under distance constraint is NP-hard. We design a dynamic-programming algorithm and an Apriori-style algorithm for finding optimal previews. Results from experiments, comparison with related work and user studies demonstrated the scoring measures' accuracy and the discovery algorithms' efficiency.Comment: This is the camera-ready version of a SIGMOD16 paper. There might be tiny differences in layout, spacing and linebreaking, compared with the version in the SIGMOD16 proceedings, since we must submit TeX files and use arXiv to compile the file

Direct mining of subjectively interesting relational patterns

Data is typically complex and relational. Therefore, the development of relational data mining methods is an increasingly active topic of research. Recent work has resulted in new formalisations of patterns in relational data and in a way to quantify their interestingness in a subjective manner, taking into account the data analyst's prior beliefs about the data. Yet, a scalable algorithm to find such most interesting patterns is lacking. We introduce a new algorithm based on two notions: (1) the use of Constraint Programming, which results in a notably shorter development time, faster runtimes, and more flexibility for extensions such as branch-and-bound search, and (2), the direct search for the most interesting patterns only, instead of exhaustive enumeration of patterns before ranking them. Through empirical evaluation, we find that our novel bounds yield speedups up to several orders of magnitude, especially on dense data with a simple schema. This makes it possible to mine the most subjectively-interesting relational patterns present in databases where this was previously impractical or impossible

Relationship based Entity Recommendation System

With the increase in usage of the internet as a place to search for information, the importance of the level of relevance of the results returned by search engines have increased by many folds in recent years. In this paper, we propose techniques to improve the relevance of results shown by a search engine, by using the kinds of relationships between entities a user is interested in. We propose a technique that uses relationships between entities to recommend related entities from a knowledge base which is a collection of entities and the relationships with which they are connected to other entities. These relationships depict more real world relationships between entities, rather than just simple “is-a” or “has-a” relationships. The system keeps track of relationships on which user is clicking and uses this click count as a preference indicator to recommend future entities. This approach is very useful in modern day semantic web searches for recommending entities of user’s interests