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Latent contextual indexing of annotated documents

Christian Sengstock, Michael Gertz
2012 Proceedings of the 21st international conference companion on World Wide Web - WWW '12 Companion  
In this paper we propose a simple and flexible framework to index context-annotated documents, e.g., documents with timestamps or georeferences, by contextual topics.  ...  Such a framework supports document clustering, labeling, and search, with respect to contextual knowledge contained in the document collection.  ...  LATENT CONTEXTUAL INDEXING We assume a context-annotated document collection, such as a set of georeferenced text documents.  ... 
doi:10.1145/2187980.2188143 dblp:conf/www/SengstockG12 fatcat:oqlqt26nejheda25ojh5gmtlqm

Evaluating Contextual Dependency of Paraphrases using a Latent Variable Model

Kiyonroi Ohtake
2005 International Workshop on Paraphrasing  
We assume that the context of a sentence is indicated by a latent variable of the model as a topic and that the likelihood of each variable can be inferred.  ...  This paper presents an evaluation method employing a latent variable model for paraphrases with their contexts.  ...  Acknowledgements This research was supported in part by the Ministry of Public Management, Home Affairs, Posts and Telecommunications.  ... 
dblp:conf/acl-iwp/Ohtake05 fatcat:zw733hqlofagjfgbfyqbdjk45y

Probabilistic models for topic learning from images and captions in online biomedical literatures

Xin Chen, Caimei Lu, Yuan An, Palakorn Achananuparp
2009 Proceeding of the 18th ACM conference on Information and knowledge management - CIKM '09  
During the indexing stage, the 'bag-of-words' representation of caption words is supplemented by an ontology-based concept indexing to alleviate the synonym and polysemy problems.  ...  We compare the performance of our model with the extension of the Correspondence LDA (Corr-LDA) model under the same biomedical image annotation scenario using cross-validation.  ...  First, we proposed a novel HPB model to integrate background information in topic learning, incorporating contextual information to interpret the uncovered latent topic and improve the image annotation  ... 
doi:10.1145/1645953.1646017 dblp:conf/cikm/ChenLAA09 fatcat:6lhjs2l5gvgjbaop5iy37prkri

Semantic Image Annotation based on Robust Probabilistic Latent Semantic Analysis

Dongping Tian
2017 Journal of Information Hiding and Multimedia Signal Processing  
In this paper, we present a robust probabilistic latent semantic analysis (PLSA) for the task of automatic image annotation.  ...  On the other hand, the traditional bag-of-visual-words model is improved by integrating the contextual semantic information among visual words based on the PLSA.  ...  PLSA, in brief, is a statistical latent class model that introduces a hidden variable (latent aspect) z k in the generative process of each element x j in a document d i .  ... 
dblp:journals/jihmsp/Tian17 fatcat:ol4spdpwxjgx3k6obdydblrf2q

A Survey on Automatic Semantic Subject Indexing of Documents using Big Data Analytics

K. Swanthana
2018 International Journal for Research in Applied Science and Engineering Technology  
To retrieve the documents which are contextually related by annotating the massive collection with only the title and abstract, whereas individual words provide unreliable evidence about the conceptual  ...  The automatic subject indexing of documents is prevailing issue due to the increase in quantity and diversity of digital documents available to end users.  ...  Probabilistic Latent Semantic Analysis (PLSA): Probabilistic Latent Semantic Indexing is a novel approach to automated document indexing which is based on a statistical latent class model for factor analysis  ... 
doi:10.22214/ijraset.2018.4282 fatcat:mki2fowtfff4jfug2mlcnkypdi

BIMTag: Concept-based automatic semantic annotation of online BIM product resources

Ge Gao, Yu-Shen Liu, Pengpeng Lin, Meng Wang, Ming Gu, Jun-Hai Yong
2017 Advanced Engineering Informatics  
Secondly, based on latent semantic analysis technique, a document-level annotation algorithm is proposed to discover the relationships which are not explicitly defined in IFC.  ...  Therefore, there is an increasing need for semantic annotation to reduce the ambiguity and unclearness of natural language in BIM documents.  ...  The research is supported by the National Science Foundation of China(61472202, 61272229) and the National Technological Support Program for the 12th-Five-Year Plan of China (2012BAJ03B07).  ... 
doi:10.1016/j.aei.2015.10.003 fatcat:mypb4efqsjedvfr4dw2epnmvlm

Cross Lingual Mention and Entity Embeddings for Cross-Lingual Entity Disambiguation

Hamed Shahbazi, Chao Ma, Xiaoli Z. Fern, Prasad Tadepalli
2016 Text Analysis Conference  
Cross-lingual Entity Discovery and Linking (EDL) task involves discovering query mentions in crosslingual documents and linking them to their referent entities in an English Knowledge Base (KB).  ...  Recently, deep learning based models have emerged as compelling solutions that alleviate the problem of feature engineering.  ...  Entity Discovery We use our last year developed annotator proposed at TAC KBP 2015 to annotate the documents.  ... 
dblp:conf/tac/ShahbaziMFT16 fatcat:opwks4k6zjb7baraesj2ux7ypy

Extended Probabilistic Latent Semantic Analysis for Automatic Image Annotation

Dongping Tian
2017 Journal of Information Hiding and Multimedia Signal Processing  
So in this paper, we propose a novel extended probabilistic latent semantic analysis (PLSA) to improve the performance of automatic image annotation.  ...  On one hand, the traditional bag-of-visual-words model is improved by integrating the contextual semantic information among visual words based on the PLSA model.  ...  Probabilistic latent semantic analysis, in brief, is a statistical latent class model that introduces a hidden variable (latent aspect) z k in the generative process of each element w i in a document d  ... 
dblp:journals/jihmsp/Tian17a fatcat:3sgydjovbvbgfdulhkj725o3eu

Combining visual features and text data for medical image retrieval using latent semantic kernels

Juan C. Caicedo, Jose G. Moreno, Edwin A. Niño, Fabio A. González
2010 Proceedings of the international conference on Multimedia information retrieval - MIR '10  
We achieve this by using Latent Semantic Kernels to generate a new representation space whose coordinates define latent concepts that merge visual patterns and textual terms.  ...  Then, a system to search using the query-by-example paradigm is evaluated instead of a keyword-based search.  ...  Then, a vector space model is built to index the frequency of document terms.  ... 
doi:10.1145/1743384.1743442 dblp:conf/mir/CaicedoMNG10 fatcat:jvbk72tepvczvmsjjdizqobzje

Improving Span-based Question Answering Systems with Coarsely Labeled Data [article]

Hao Cheng, Ming-Wei Chang, Kenton Lee, Ankur Parikh, Michael Collins, Kristina Toutanova
2018 arXiv   pre-print
Experiments demonstrate that the standard multi-task learning approach of sharing representations is not the most effective way to leverage coarse-grained annotations.  ...  We study approaches to improve fine-grained short answer Question Answering models by integrating coarse-grained data annotated for paragraph-level relevance and show that coarsely annotated data can bring  ...  The input x to both tasks is a question-document pair. Each document is a sequence of M paragraphs, and each paragraph with index p (where 1 ≤ p ≤ M ) is a sequence of n p tokens.  ... 
arXiv:1811.02076v1 fatcat:55fatqcagfgnppnfxcr3ku2jha

Semantic-inspired Contextual Affect Detection from Drama Improvisation

Li Zhang, Alamgir Hossain
2012 Procedia Computer Science  
Topic theme detection using latent semantic analysis has been applied to such inputs to identify their discussion themes and potential target audiences.  ...  Such semantic interpretation of the dialogue context also shows great potential in the recognition of metaphorical phenomena and the development of a personalized intelligent tutor for drama improvisation  ...  Latent semantic analysis generally identifies relationships between a set of documents and the terms they contain by producing a set of concepts related to the documents and terms.  ... 
doi:10.1016/j.procs.2012.06.039 fatcat:hsq7vonz6rfann2w2yt6xlz5u4

Incorporating Content Structure into Text Analysis Applications

Christina Sauper, Aria Haghighi, Regina Barzilay
2010 Conference on Empirical Methods in Natural Language Processing  
We present a framework which combines a supervised text analysis application with the induction of latent content structure. Both of these elements are learned jointly using the EM algorithm.  ...  This follows the linguistic intuition that rich contextual information should be useful in these tasks.  ...  Any opinions, findings, conclusions, or recommendations expressed in this paper are those of the authors, and do not necessarily reflect the views of the funding organizations.  ... 
dblp:conf/emnlp/SauperHB10 fatcat:fa62kdrbvndxblwfhhc77juyuu

Improving Large-Scale k-Nearest Neighbor Text Categorization with Label Autoencoders

Francisco J. Ribadas-Pena, Shuyuan Cao, Víctor M. Darriba Darriba Bilbao
2022 Mathematics  
In this paper, we introduce a multi-label lazy learning approach to deal with automatic semantic indexing in large document collections in the presence of complex and structured label vocabularies with  ...  the predicted labels from this latent space.  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/math10162867 fatcat:jhatrtirmvgpjnu3z33ok4naci

Time-aware topic-based contextualization

Nam Khanh Tran
2014 Proceedings of the 23rd International Conference on World Wide Web - WWW '14 Companion  
While human can smoothly interpret documents when they have knowledge of the context of documents, they have difficulty with those as their context is lost or changes.  ...  In this PhD proposal, we address three novel research questions: detecting uninterpretable pieces in documents, retrieving contextual information and constructing compact context for the documents, then  ...  In recent years, topic modeling is an area in machine learning that discovers the latent "topic" (represented by a group of works -textual or visual) implied by a collection of documents.  ... 
doi:10.1145/2567948.2567957 dblp:conf/www/Tran14 fatcat:ho6r3rszlrfh7hzjleplrczqha

Usingtagflakefor condensing navigable tag hierarchies from tag clouds

Luigi Di Caro, K. Selçuk Candan, Maria Luisa Sapino
2008 Proceeding of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD 08  
of documents.  ...  This provides tagFlake with a mechanism for enabling navigation within the tag space and for classification of the text documents based on the contextual structure captured by the created hierarchy. tagFlake  ...  Tags, whether provided by the user or extracted from the textual content, annotate online documents (such as blogs and news articles) with popular terms, thus providing an easy way to search and index  ... 
doi:10.1145/1401890.1402021 dblp:conf/kdd/CaroCS08 fatcat:5ozpql7xh5dvlhpkwrzvpfss6a
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