Existing methods on knowledge base question generation (KBQG) learn a one-size-fits-all model by training together all subgraphs without distinguishing the diverse semantics of subgraphs. In this work, we show that ma...
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For ontology-based applications, the efficiency of ontology query is vital. Different from existing approaches, the paper improves performance of ontology query by materializing some derived relations. Experimental re...
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Genealogical knowledge graphs depict the relationships of family networks and the development of family histories. They can help researchers to analyze and understand genealogical data, search for genealogical descend...
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User profiling by inferring user personality traits,such as age and gender,plays an increasingly important role in many real-world *** existing methods for user profiling either use only one type of data or ignore han...
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User profiling by inferring user personality traits,such as age and gender,plays an increasingly important role in many real-world *** existing methods for user profiling either use only one type of data or ignore handling the noisy information of ***,they usually consider this problem from only one *** this paper,we propose a joint user profiling model with hierarchical attention networks(JUHA)to learn informative user representations for user *** JUHA method does user profiling based on both inner-user and inter-user *** explore inner-user features from user behaviors(e.g.,purchased items and posted blogs),and inter-user features from a user-user graph(where similar users could be connected to each other).JUHA learns basic sentence and bag representations from multiple separate sources of data(user behaviors)as the first round of data *** this module,convolutional neural networks(CNNs)are introduced to capture word and sentence features of age and gender while the self-attention mechanism is exploited to weaken the noisy *** this,we build another bag which contains a user-user ***-user features are learned from this bag using propagation information between linked users in the *** acquire more robust data,inter-user features and other inner-user bag representations are joined into each sentence in the current bag to learn the final bag ***,all of the bag representations are integrated to lean comprehensive user representation by the self-attention *** experimental results demonstrate that our approach outperforms several state-of-the-art methods and improves prediction performance.
Fuel cells are made from fuel and *** of its low pollution,high energy conversion efficiency and high reliability,fuel cell has become the future direction of new energy application,the technological development path ...
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Fuel cells are made from fuel and *** of its low pollution,high energy conversion efficiency and high reliability,fuel cell has become the future direction of new energy application,the technological development path in the field of fuel cell research has great significance to the development of technological and energy *** the patent analysis method,this paper analyses the patent data from Derwent Innovation Index quantitively to study the state of application for patents,core technologies,highly cited patents and the main *** shows that auxiliary device and related methods were a research hotspot in recent years;as the biggest patent holder of fuel cell technologies,Toyota,Honda motor *** Nissan motor *** an *** paper has discovered some potential problems behind the phenomena and some suggestions are put forward finally.
Audio-Visual Question Answering (AVQA) is a challenging multimodal reasoning task requiring intelligent systems to answer natural language queries based on paired audio-video inputs accurately. However, existing AVQA ...
Recently, social tagging systems become more and more popular in many Web 2.0 applications. In such systems, Users are allowed to annotate a particular resource with a freely chosen a set of tags. These user-generated...
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in this paper, we analyse the data access characteristics of a typical XML information retrieval system and propose a new query aware buffer replacement algorithm based on prediction of Minimum Reuse Distance (MRD for...
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The volume of RDF data increases dramatically within recent years, while cloud computing platforms like Hadoop are supposed to be a good choice for processing queries over huge data sets for their wonderful scalabilit...
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The volume of RDF data increases dramatically within recent years, while cloud computing platforms like Hadoop are supposed to be a good choice for processing queries over huge data sets for their wonderful scalability. Previous work on evaluating SPARQL queries with Hadoop mainly focus on reducing the number of joins through careful split of HDFS files and algorithms for generating Map/Reduce jobs. However, the way of partitioning RDF data could also affect system performance. Specifically, a good partitioning solution would greatly reduce or even to- tally avoid cross-node joins, and significantly cut down the cost in query evaluation. Based on HadoopDB, this work processes SPARQL queries in a hybrid architecture, where Map/Reduce takes charge of the computing tasks, and RDF query engines like RDF-3X store the data and execute join operations. According to the analysis of query workloads, this work proposes a novel algorithm for automatically parti- tioning RDF data and an approximate solution to physically place the partitions in order to reduce data redundancy. It also discusses how to make a good trade-off between query evaluation efficiency and data redundancy. All of these pro- posed approaches have been evaluated by extensive experiments over large RDF data sets.
Text classification is an important task in natural language processing. Different from English, Chinese text owns two representations, character-level and word-level. The former has abundant connotations and the latt...
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