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Examining drug and side effect relation using author-entity pair bipartite networks

JOURNAL OF INFORMETRICS 2020年第1期14卷 100999-000页

作者： Jeong, Yoo Kyung Xie, Qing Yan, Erjia Song, Min Yonsei Univ Ctr Modern Korean Studies Wonju South Korea Yonsei Univ Dept Lib & Informat Sci Seoul South Korea Drexel Univ Coll Comp & Informat Philadelphia PA 19104 USA

The current study has two objectives. First, we explore the characteristics of biological entities, such as drugs, and their side effects using an author-entity pair bipartite network. Second, we use the constructed network to examine whether there are outstanding features of relations between drugs and side effects. We extracted drug and side effect names from 169,766 PubMed abstracts published between 2010 to 2014 and constructed author-entity pair bipartite networks after ambiguous author names were processed. We propose a new ranking algorithm that takes into consideration the characteristics of bipartite networks to identify top-ranked biological drug and side effect pairs. To investigate the relationship between a particular drug and a side effect, we compared the drug and side effect pairs obtained from the network containing both drug and side effect with those observed in SIDER, a human expert-curated database. The results of this study indicate that our approach was able to identify a wide range of patterns of drug-side effect relations from the perspective of authors' research interests. Further, our approach also identified the unique characteristics of the relation of biomedical entities obtained using an author-entity pair bipartite network. (C) 2019 Elsevier Ltd. All rights reserved.

关键词： Bipartite network ranking algorithm Knowledge structure Knowledge discovery Biological entity relation

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A user-centric semantic-based algorithm for ranking services: design and analysis

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SERVICE ORIENTED COMPUTING AND APPLICATIONS 2017年第1期11卷 101-120页

作者： Alsaig, Ammar Alagar, Vangalur Mohammad, Mubarak Alhalabi, Wadee Concordia Univ Dept Comp Sci & Software Engn Montreal PQ Canada King Abdulaziz Univ Dept Comp Sci Jeddah Saudi Arabia

The number of online service providers and services hosted by them is rapidly increasing. Since services hosted by different service providers may have the same functionality, it is extremely hard for a user to determine those services that best match their requirements. To ease this difficulty, it is necessary that the service providing system rank those services based on users preferences, so that users receive only those services that suit them best. In this paper, a novel vector-based algorithm, which is multi-featured, semantic-based, and user-centric, is proposed for this service ranking problem. This algorithm overcomes all restrictions and limitations that exist in previously known vector-based ranking algorithms. The algorithm has been analyzed thoroughly with respect to performance, accuracy, and algorithmic complexity.

关键词： Service-oriented system User-centric preferences Semantics Fair ranking ranking algorithm

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BM25-AH: Enhanced BM25 algorithm for Domain-Specific Search Engine 21

BM25-AH: Enhanced BM25 Algorithm for Domain-Specific Search ...

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21st International Conference on Information Integration and Web-Based Applications and Services (iiWAS)

作者： Kalian, Kirk Remig, Charles Jung, Youna Virginia Mil Inst Comp & Informat Sci Lexington VA 24450 USA

ISBN: (纸本)9781450371797

The Virginia Military Institute (VMI) uses Google search to provide webpage search service in the VMI website. As Google search is a general-purpose service, it does not consider VMI-specific information and in turn, often fails to retrieve relevant information. To address the limitation, in this paper, we propose the BM25-AH algorithm, an extension of the BM25 ranking algorithm that utilizes domain-specific knowledge by adding four new features to the existing BM25 algorithm. The implementation results show us the potential of the proposed algorithm and the new VMI search engine.

关键词： Search Engine Information Retrieval ranking algorithm Indexing BM25

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ranking ON ARBITRARY GRAPHS: REMATCH VIA CONTINUOUS LINEAR PROGRAMMING

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SIAM JOURNAL ON COMPUTING 2018年第4期47卷 1529-1546页

作者： Chan, T-H Hubert Chen, Fei Wu, Xiaowei Zhao, Zhichao Univ Hong Kong Dept Comp Sci Hong Kong Hong Kong Peoples R China

Motivated by online advertisement and exchange settings, greedy randomized algorithms for the maximum matching problem have been studied, in which the algorithm makes (random) decisions that are essentially oblivious to the input graph. Any greedy algorithm can achieve a performance ratio of 0.5, which is the expected number of matched nodes to the number of nodes in a maximum matching. Since Aronson, Dyer, Frieze, and Suen [Random Structures algorithm, 6 (1991), pp. 29-46] proved that the modified randomized greedy algorithm achieves a performance ratio of 0:5 + epsilon (where epsilon = 1/400000) on arbitrary graphs in the midnineties, no further attempts in the literature have been made to improve this theoretical ratio for arbitrary graphs until two papers were published in FOCS 2012 [G. Goel and P. Tripathi, IEEE Computer Society, Los Alamitos, CA, 2012, pp. 718-727;M. Poloczek and M. Szegedy, IEEE Computer Society, Los Alamitos, CA, 2012, pp. 708-717]. In this paper, we revisit the ranking algorithm using the linear programming framework. Special care is given to analyze the structural properties of the ranking algorithm in order to derive the linear programming constraints, of which one known as the boundary constraint requires totally new analysis and is crucial to the success of our linear program (LP). We use continuous linear programming relaxation to analyze the limiting behavior as the finite LP grows. Of particular interest are new duality and complementary slackness characterizations that can handle the monotone and the boundary constraints in continuous linear programming. Improving previous work, this paper achieves a theoretical performance ratio of 2(5-root 7)/9 approximate to 0.523 on arbitrary graphs.

关键词： oblivious matching problem continuous linear programming ranking algorithm

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Toward Improving Similar Item Recommendation for a C2C Marketplace 11

Toward Improving Similar Item Recommendation for a C2C Marke...

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11th International Conference on Advanced Computer Science and Information Systems (ICACSIS)

作者： Evalina, Lisbeth Riaddy, Aditya Iftikar Savitri, Septiviana Permadi, Reza Aditya PT Bukalapak Com Bukalapak AI R&D Jakarta Indonesia

ISBN: (纸本)9781728152929

This study stems from actual challenges that we face in building a recommender system at Bukalapak. Our existing recommendation system, which is an item-to-item collaborative filtering based on co-view method has helped users during their shopping journey by offering them similar items recommendation in the product detail page. However, our baseline system has not utilized the information on how the user perceives the recommendation offered in our recommendation widget. This paper discusses how we improve our recommendation system with point-wise Learning-to-Rank (LTR) method. We also present specific features that support the LTR performance. Finally, we evaluate the LTR model by offline evaluation metrics and online A/B test, where we compare our baseline by using the model to rerank the candidates item before presenting them as recommendation sets. By calculating the Click Through Rate (CTR), it shows that the LTR method can outperform the baseline by 1.63%.

关键词： recommender system ranking algorithm e-commerce

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A Fistful of Votes: Understanding the Voting System in Social Question and Answer Websites 10

A Fistful of Votes: Understanding the Voting System in Socia...

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10th IFIP International Conference on New Technologies, Mobility and Security (NTMS)

作者： Zhang, Jun Labiod, Houda Meng, Weizhi Telecom ParisTech INFRES Paris France Tech Univ Denmark Dept Appl Math & Comp Sci Lyngby Denmark

ISBN: (纸本)9781728115429

Recently, there is an increasing trend that people start sharing their comments in online question and answer (QA) websites. For such websites, the ranking of answers is usually determined based on several factors like the received upvotes and downvotes, the publishing time, and the reputation of users, such that a highly ranked answer has much more chances to be propagated over the Internet. Due to the popularity of these QA websites, some public relationship companies try to cheat users by promoting or blocking certain answers. In this paper, we take Quora and Zhihu as two case studies to understand the impact of follower numbers, the publishing time, the upvotes and downvotes on the ranking of answers, and to investigate how these websites are vulnerable to voting spammers. Meanwhile, we propose a scheme to estimate the list of downvotes, which is usually hidden behind such websites.

关键词： Social networks question and answer community ranking algorithm spammer

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Tackling Information Asymmetry in Networks: A New Entropy-Based ranking Index

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JOURNAL OF STATISTICAL PHYSICS 2018年第3-4期173卷 1028-1044页

作者： Barucca, Paolo Caldarelli, Guido Squartini, Tiziano Univ Zurich Dept Banking & Finance Zurich Switzerland London Inst Math Sci 35a South St London W1K 2XF England IMT Sch Adv Studies Pzza S Francesco 19 I-55100 Lucca Italy

Information is a valuable asset in socio-economic systems, a significant part of which is entailed into the network of connections between agents. The different interlinkages patterns that agents establish may, in fact, lead to asymmetries in the knowledge of the network structure;since this entails a different ability of quantifying relevant, systemic properties (e.g. the risk of contagion in a network of liabilities), agents capable of providing a better estimation of (otherwise) inaccessible network properties, ultimately have a competitive advantage. In this paper, we address the issue of quantifying the information asymmetry of nodes: to this aim, we define a novel indexInfoRankintended to rank nodes according to their information content. In order to do so, each node ego-network is enforced as a constraint of an entropy-maximization problem and the subsequent uncertainty reduction is used to quantify the node-specific accessible information. We, then, test the performance of our ranking procedure in terms of reconstruction accuracy and show that it outperforms other centrality measures in identifying the most informative nodes. Finally, we discuss the socio-economic implications of network information asymmetry.

关键词： Complex networks Shannon entropy Information theory ranking algorithm

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BM25-AH: Enhanced BM25 algorithm for Domain-Specific Search Engine 2019

BM25-AH: Enhanced BM25 Algorithm for Domain-Specific Search ...

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Proceedings of the 21st International Conference on Information Integration and Web-based Applications & Services

作者： Kirk Kalian Charles Remig Youna Jung Computer and Information Sciences Virginia Military Institute Lexington VA United States

ISBN: (纸本)9781450371797

关键词： Search Engine Information Retrieval ranking algorithm BM25 Indexing

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Design a batched information retrieval system based on a concept-lattice-like structure

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KNOWLEDGE-BASED SYSTEMS 2018年 150卷 74-84页

作者： Huang, Ming Lin, Jiajun Peng, Yong Xie, Xing East China Univ Sci & Technol Shanghai 200237 Peoples R China Colorado State Univ Ft Collins CO 80523 USA Beijing Univ Posts & Telecommun Beijing 100876 Peoples R China

Nowadays, as is envisioned as one of the most popular and challenging research areas due to the rapid growth of web data, information retrieval (IR) serves as a fundamental technology in large scale dataset processing and analyzing. IR systems usually involve handling massive and continuous retrieval requests in data matching, information filtering and other application scenarios. However, in the general applications of IR such as search engines, the individual response time is mostly emphasized and the efficiency of handling massive queries mainly relies on caching or similar technologies. For improving the overall efficiency of handling massive queries, we design a batched information retrieval system which first analyzes a batch of queries and then utilizes the repeats, similarity and correlations among queries to accelerate the retrievals. A concept-lattice-like structure called keyword-DAG (Directed Acyclic Graph) is first exploited to store and organize the similarity among queries. Accordingly a keyword-DAG processing algorithm namely pruning is devised to implement the batched retrieval. Then an incremental ranking algorithm is presented for the batched IR scenarios, which has be demonstrated (both in theory and practice) to be able to remarkably shorten the retrieval time. Finally, an overall planning algorithm is proposed for choosing the optimal pruning path and improving the utilization of memory. The experiment results show that our approach embraces far better performance compared with the traditional separate retrieval method in mass data processing and analyzing scenarios. (C) 2018 Elsevier B.V. All rights reserved.

关键词： Information retrieval Information filtering Concept lattice Inverted file ranking algorithm Caching

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Hesitant Fuzzy Linguistic Group DEMATEL Method with Multi-granular Evaluation Scales

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INTERNATIONAL JOURNAL OF FUZZY SYSTEMS 2018年第7期20卷 2187-2201页

作者： Han, Wei Sun, Yonghe Xie, Hui Che, Zhimin Kunming Univ Sci & Technol Fac Econ & Management Kunming 650093 Yunnan Peoples R China Kunming Univ Sci & Technol City Coll Kunming 650051 Yunnan Peoples R China

Decision-making trial and evaluation laboratory is a widely applied method used in the research of complicated socioeconomic system issues. However, this traditional method is not feasible when experts are non-homogeneous and hesitant between two or more statements. In this paper, hesitant fuzzy linguistic term sets (HFLTSs) are applied to facilitate the experts' expressions with regard to a direct influence level between factors, in order to analyze the causal relationship of the relevant system. Experts can use a linguistic expression (which is close to human expression) to show their opinions, which can be easily transferred into HFLTSs. Meanwhile, by using the concept of regarding the influence between factors as object and the level of influence as criteria, this paper proposes a comparison-based ranking algorithm to cope with the aggregation process of multi-granular scaled evaluation. In the algorithm, two adjustable possibility thresholds are introduced to control the output granule of the group consensus direct-influence scores. The validity and effectiveness of the proposed approach are finally demonstrated through an illustrative example and analysis.

关键词： Decision-making trial and evaluation laboratory Hesitant fuzzy linguistic term sets Multi-granular ranking algorithm

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