Jiamin Lu

Jiamin Lu
Hohai University · College of Computer and Information Technology Engineering

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30
Publications
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219
Citations

Publications

Publications (30)
Article
Event detection (ED) is a task that requires capturing deep semantic information in text to correctly identify specific types of events. Semantic dependency graph aims to recover sentence-internal predicate-argument relationships. However, recent ED researches often use syntactic dependency tree in GNNs, while we believe that the semantic dependenc...
Article
Full-text available
Relation extraction aims to identify semantic relations between entities in text. In recent years, this task has been extended to the joint extraction of entities and relations, which requires the simultaneous identification of entities and their relations from sentences. However, existing methods, limited by the existing tagging scheme, fail to id...
Conference Paper
Full-text available
Inferring causal relationships is key to data science. Learning causal structures in the form of directed acyclic graphs (DAGs) has been widely adopted for uncovering causal relationships, nonetheless, it is a challenging task owing to its exponential search space. A recent approach formulates the structure learning problem as a continuous constrai...
Article
Efficient scheduling algorithms are key for attaining high performance in heterogeneous computing systems. In this article, we propose a new list scheduling algorithm for assigning task graphs to fully connected heterogeneous processors with an aim to minimize the scheduling length. The proposed algorithm, called Improved Predict Priority Task Sche...
Article
Full-text available
Hierarchical topic models, such as hierarchical Latent Dirichlet Allocation (hLDA)and its variations, can organize topics into a hierarchy automatically. On the other hand, there are lots of documents associated with hierarchical label information. Incorporating these information into the topic modeling process can help users to obtain a more reaso...
Conference Paper
This paper presents a list-based scheduling algorithm called Predict Priority Task Scheduling (PPTS) for heterogeneous computing. The main goal is to minimize the scheduling length by introducing a lookahead feature in the two phases of the PPTS algorithm, namely the task prioritizing phase and the processor selection phase. Existing list schedulin...
Chapter
Although several methods have been developed in the past to discover the truth from conflicting data sources, many of them share the drawback of assigning the same default weight to all data sources in the beginning of truth discovery, without introducing any a priori knowledge concerning the data sources. This weakness limits the applicability of...
Article
During the process of smart city construction, city managers always spend a lot of energy and money cleaning street garbage due to the random appearances of street garbage. Consequently, visual street cleanliness assessment is particularly important. However, existing assessment approaches have some clear disadvantages, such as the collection of st...
Article
The range query of moving objects in a road network is widely used in battlefield environment, intelligent transportation systems, and mobile phone location. It has gradually become a research hotspot in the field of spatiotemporal data management. Most of the existing research on range query of moving objects in the road network is based on the pr...
Conference Paper
In recent years, many researchers have paid attention to skyline queries in road network. The continuous skyline queries for moving objects are particularly complex, especially when we consider the moving query point. Existing studies mainly focus on objects search bound and distance calculation, aiming to reduce the cost of repetitive dominant com...
Article
Currently, LBS (location-based service) is widely employed in many mobile devices, making the technology for processing moving object data underlying the road network to become a research hotspot in the community of spatio-temporal processing techniques. This paper intends to survey the previous work from three aspects including index structures, q...
Conference Paper
Along with the continuous development of the cloud computing technology, many Cloud Service Providers (CSPs) come forth to offer computing infrastructures, often called instances, online. In order to help the users to select their required services, this paper proposes a cloud performance evaluation model, based on the assess results obtained from...
Conference Paper
Collaborative filtering, a successful and wildly used technique in personalized recommender systems, generates recommendations by similar users. Cosine similarity and Pearson correlation coefficient are widely used in collaborative filtering to calculate the similarity; however, the similarity is not accurate in some cases because of the defects of...
Article
As data stream grows exponentially, the aggregate query technique is widely used since it can rapidly obtain the summary information. Typical approximate aggregate query methods, like sliding-window, random sampling, wavelet, sketch index structure, histogram, etc., all evaluate the quality of the algorithms by the average size of query errors and...
Article
Secondo is an extensible DBMS prototype. It emphasizes the handling of spatial and moving objects data and provides sophisticated data models and query processing over such data, offering specialized types and operations. More generally, there is a wealth of techniques available, for example, (i) construction of a road network from OpenStreetMap da...
Conference Paper
Parallel Secondo scales up the capability of processing extensible data models in Secondo. It combines Hadoop with a set of Secondo databases, providing almost all existing SECONDO data types and operators. Therefore it is possible for the user to convert large-scale sequential queries to parallel queries without learning the Map/Reduce programming...
Article
Along with the increasing Big Data challenges, the MapReduce based systems are extensively welcomed, because of their remarkable simplicity and scalability. However, from the first day MapReduce is proposed, its argument with parallel DBMSs never stops, as it over-focuses on the scalability but overlooks the efficiency. Accordingly, extended system...
Conference Paper
This paper presents a hybrid parallel processing system, named Parallel Secondo. It combines the Hadoop framework and a set of single-computer Secondo databases, in order to introduce the mobility data procedures into the parallel processing community, and vice versa. The system keeps the front-end and the executable language of Secondo to allow th...
Conference Paper
The growing need of processing massive amounts of data leads database researchers to explore the possibility of combining their existing single-computer database systems with the popular parallel processing platform Hadoop. These hybrid systems not only can keep the efficiency of database processing, but also achieve a remarkable scalability. This...
Conference Paper
Hadoop is an efficient and simple parallel framework following the Map Reduce paradigm, and making the parallel processing recently become a hot issue in data-intensive applications. Since Hadoop can be easily deployed on large-scale clusters including up to thousands of computers, various studies intend to process common relational database operat...
Conference Paper
In the past composite structures for managing road network-constrained moving objects, the road network is usually broken up into road segments. This scheme will cause high concentrated update operations, and some needless queries while tracking the moving objects. In this paper, we propose a new unit called cross region(CR) to break up the road ne...
Article
The past composite structures for managing spatio-temporal data based on the road network usually use road segment as units to divide moving objects into different groups. This scheme causes inaccurate description about vehicles' current segments, and also takes high update cost caused by R-Tree's inherent property. In this paper, we propose an imp...
Conference Paper
Composite structures are proposed to index moving objects in road network. However, there are many problems for indexing moving objects for current and forecasting queries on road network, efficiently. This paper proposes methods for improving such kinds of structure, and gives a new structure R-TPR± Tree. Evaluation shows the new structure outperf...

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