Knowledge representation learning with entity descriptions,hierarchical types,and textual relations     

Xing Tang  Ling Chen  Jun Cui  Baogang Wei 《Information processing & management》2019,56(3):809-822

  相似文献   

Neural embedding-based indices for semantic search     

Fatemeh Lashkari  Ebrahim Bagheri  Ali A. Ghorbani 《Information processing & management》2019,56(3):733-755

Traditional information retrieval techniques that primarily rely on keyword-based linking of the query and document spaces face challenges such as the vocabulary mismatch problem where relevant documents to a given query might not be retrieved simply due to the use of different terminology for describing the same concepts. As such, semantic search techniques aim to address such limitations of keyword-based retrieval models by incorporating semantic information from standard knowledge bases such as Freebase and DBpedia. The literature has already shown that while the sole consideration of semantic information might not lead to improved retrieval performance over keyword-based search, their consideration enables the retrieval of a set of relevant documents that cannot be retrieved by keyword-based methods. As such, building indices that store and provide access to semantic information during the retrieval process is important. While the process for building and querying keyword-based indices is quite well understood, the incorporation of semantic information within search indices is still an open challenge. Existing work have proposed to build one unified index encompassing both textual and semantic information or to build separate yet integrated indices for each information type but they face limitations such as increased query process time. In this paper, we propose to use neural embeddings-based representations of term, semantic entity, semantic type and documents within the same embedding space to facilitate the development of a unified search index that would consist of these four information types. We perform experiments on standard and widely used document collections including Clueweb09-B and Robust04 to evaluate our proposed indexing strategy from both effectiveness and efficiency perspectives. Based on our experiments, we find that when neural embeddings are used to build inverted indices; hence relaxing the requirement to explicitly observe the posting list key in the indexed document: (a) retrieval efficiency will increase compared to a standard inverted index, hence reduces the index size and query processing time, and (b) while retrieval efficiency, which is the main objective of an efficient indexing mechanism improves using our proposed method, retrieval effectiveness also retains competitive performance compared to the baseline in terms of retrieving a reasonable number of relevant documents from the indexed corpus.  相似文献   

Triggering effects of mobile video marketing in nature tourism: Media richness perspective     

Ari Alamäki  Juho Pesonen  Amir Dirin 《Information processing & management》2019,56(3):756-770

The aim of this study was to investigate videos as potential triggers of behavior. Therefore, we applied the theories of triggers and media richness to learn about the triggering efficiency of mobile marketing videos on participants’ behavioral intentions. The experiment involved three distinct test groups, each comprising 41 student participants. From the perspective of media richness theory, we observed that the different kinds of videos had quite similar effects in terms of triggering behavioral changes. However, the mechanisms explaining why triggers were present differed for each video. Further, the results reveal that the consumer's position in the information search process was the most significant reason for the triggering of any kind of effect. In addition, the instructionally designed videos were able to exert an affective triggering effect: the more participants liked the video, the more it affected their participation intention and recall scores. This study extends the media richness research by demonstrating that the effects of media richness can vary within technically similar videos, as they form different logical connections among non-verbal visual cues related to a video's storyline.  相似文献   

Advanced Arabic Natural Language Processing (ANLP) and its applications: Introduction to the special issue     

Yaser Jararweh  Mahmoud Al-Ayyoub  Elhadj Benkhelifa 《Information processing & management》2019,56(2):259-261

  相似文献   

Understanding the topic evolution of scientific literatures like an evolving city: Using Google Word2Vec model and spatial autocorrelation analysis     

Kai Hu  Qing Luo  Kunlun Qi  Siluo Yang  Jin Mao  Xiaokang Fu  Jie Zheng  Huayi Wu  Ya Guo  Qibing Zhu 《Information processing & management》2019,56(4):1185-1203

Topic evolution has been described by many approaches from a macro level to a detail level, by extracting topic dynamics from text in literature and other media types. However, why the evolution happens is less studied. In this paper, we focus on whether and how the keyword semantics can invoke or affect the topic evolution. We assume that the semantic relatedness among the keywords can affect topic popularity during literature surveying and citing process, thus invoking evolution. However, the assumption is needed to be confirmed in an approach that fully considers the semantic interactions among topics. Traditional topic evolution analyses in scientometric domains cannot provide such support because of using limited semantic meanings. To address this problem, we apply the Google Word2Vec, a deep learning language model, to enhance the keywords with more complete semantic information. We further develop the semantic space as an urban geographic space. We analyze the topic evolution geographically using the measures of spatial autocorrelation, as if keywords are the changing lands in an evolving city. The keyword citations (keyword citation counts one when the paper containing this keyword obtains a citation) are used as an indicator of keyword popularity. Using the bibliographical datasets of the geographical natural hazard field, experimental results demonstrate that in some local areas, the popularity of keywords is affecting that of the surrounding keywords. However, there are no significant impacts on the evolution of all keywords. The spatial autocorrelation analysis identifies the interaction patterns (including High-High leading, High-Low suppressing) among the keywords in local areas. This approach can be regarded as an analyzing framework borrowed from geospatial modeling. Moreover, the prediction results in local areas are demonstrated to be more accurate if considering the spatial autocorrelations.  相似文献   

Writer identification approach based on bag of words with OBI features     

Amal Durou  Ibrahim Aref  Somaya Al-Maadeed  Ahmed Bouridane  Elhadj Benkhelifa 《Information processing & management》2019,56(2):354-366

Handwriter identification aims to simplify the task of forensic experts by providing them with semi-automated tools in order to enable them to narrow down the search to determine the final identification of an unknown handwritten sample. An identification algorithm aims to produce a list of predicted writers of the unknown handwritten sample ranked in terms of confidence measure metrics for use by the forensic expert will make the final decision.Most existing handwriter identification systems use either statistical or model-based approaches. To further improve the performances this paper proposes to deploy a combination of both approaches using Oriented Basic Image features and the concept of graphemes codebook. To reduce the resulting high dimensionality of the feature vector a Kernel Principal Component Analysis has been used. To gauge the effectiveness of the proposed method a performance analysis, using IAM dataset for English handwriting and ICFHR 2012 dataset for Arabic handwriting, has been carried out. The results obtained achieved an accuracy of 96% thus demonstrating its superiority when compared against similar techniques.  相似文献   

In (Big) Data we trust: Value creation in knowledge organizations - Introduction to the special issue     

Andrea De Mauro  Marco Greco  Michele Grimaldi  Paavo Ritala 《Information processing & management》2018,54(5):755-757

  相似文献   

出版产业化环境下编辑决策的作者意识     

周国清 《湖南城市学院学报》2011,32(5)

出版产业化环境下编辑决策要牢固树立作者意识,这是由作者及其文稿在编辑活动中的重要位置与独特作用决定的。它要求编辑主体树立与作者平等相处的理念;深入研究和准确把握作者心理;善于、敢于、巧于接受来自作者的挑战;具有善待作者的慧眼与能耐。  相似文献   

国际学术出版开放式访问(OA):Ⅱ.开放访问期刊"作者付费模式"的实践与争论   总被引：3，自引：2，他引：1  

李若溪  Fytton Rowland 《编辑学报》2006,18(4):315-318

综述当前国际学术出版界开放访问(OA)运动实践和理论研究的热点问题之一--OA期刊的"作者付费模式".讨论该经营模式的收费来源和方式,经营成本估算和现行的价格标准.对比了OA期刊与传统期刊的经营模式的区别和利弊,分析了OA期刊的可持续发展存在的问题.  相似文献   

An efficient page ranking approach based on vector norms using sNorm(p) algorithm     

Shubham Goel  Ravinder Kumar  Munish Kumar  Vikram Chopra 《Information processing & management》2019,56(3):1053-1066

In the whole world, the internet is exercised by millions of people every day for information retrieval. Even for a small to smaller task like fixing a fan, to cook food or even to iron clothes persons opt to search the web. To fulfill the information needs of people, there are billions of web pages, each having a different degree of relevance to the topic of interest (TOI), scattered throughout the web but this huge size makes manual information retrieval impossible. The page ranking algorithm is an integral part of search engines as it arranges web pages associated with a queried TOI in order of their relevance level. It, therefore, plays an important role in regulating the search quality and user experience for information retrieval. PageRank, HITS, and SALSA are well-known page ranking algorithm based on link structure analysis of a seed set, but ranking given by them has not yet been efficient. In this paper, we propose a variant of SALSA to give sNorm(p) for the efficient ranking of web pages. Our approach relies on a p-Norm from Vector Norm family in a novel way for the ranking of web pages as Vector Norms can reduce the impact of low authority weight in hub weight calculation in an efficient way. Our study, then compares the rankings given by PageRank, HITS, SALSA, and sNorm(p) to the same pages in the same query. The effectiveness of the proposed approach over state of the art methods has been shown using performance measurement technique, Mean Reciprocal Rank (MRR), Precision, Mean Average Precision (MAP), Discounted Cumulative Gain (DCG) and Normalized DCG (NDCG). The experimentation is performed on a dataset acquired after pre-processing of the results collected from initial few pages retrieved for a query by the Google search engine. Based on the type and amount of in-hand domain expertise 30 queries are designed. The extensive evaluation and result analysis are performed using MRR, [email protected], MAP, DCG, and NDCG as the performance measuring statistical metrics. Furthermore, results are statistically verified using a significance test. Findings show that our approach outperforms state of the art methods by attaining 0.8666 as MRR value, 0.7957 as MAP value. Thus contributing to the improvement in the ranking of web pages more efficiently as compared to its counterparts.  相似文献