-
Zeng, Q.; Yu, M.; Yu, W.; Xiong, J.; Shi, Y.; Jiang, M.: Faceted hierarchy : a new graph type to organize scientific concepts and a construction method (2019)
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- Content
- Vgl.: https%3A%2F%2Faclanthology.org%2FD19-5317.pdf&usg=AOvVaw0ZZFyq5wWTtNTvNkrvjlGA.
-
Bouidghaghen, O.; Tamine, L.: Spatio-temporal based personalization for mobile search (2012)
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- Abstract
- The explosion of the information available on the Internet has made traditional information retrieval systems, characterized by one size fits all approaches, less effective. Indeed, users are overwhelmed by the information delivered by such systems in response to their queries, particularly when the latter are ambiguous. In order to tackle this problem, the state-of-the-art reveals that there is a growing interest towards contextual information retrieval (CIR) which relies on various sources of evidence issued from the user's search background and environment, in order to improve the retrieval accuracy. This chapter focuses on mobile context, highlights challenges they present for IR, and gives an overview of CIR approaches applied in this environment. Then, the authors present an approach to personalize search results for mobile users by exploiting both cognitive and spatio-temporal contexts. The experimental evaluation undertaken in front of Yahoo search shows that the approach improves the quality of top search result lists and enhances search result precision.
- Date
- 20. 4.2012 13:19:22
- Source
- Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a
-
Stamou, G.; Chortaras, A.: Ontological query answering over semantic data (2017)
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- Abstract
- Modern information retrieval systems advance user experience on the basis of concept-based rather than keyword-based query answering.
- Pages
- S.29-63
- Series
- Lecture Notes in Computer Scienc;10370) (Information Systems and Applications, incl. Internet/Web, and HCI
-
Toms, E.G.: Task-based information searching and retrieval (2011)
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- Date
- 7. 1.2013 19:29:54
- Source
- Interactive information seeking, behaviour and retrieval. Eds.: Ruthven, I. u. D. Kelly
-
Andrade, T.C.; Dodebei, V.: Traces of digitized newspapers and bom-digital news sites : a trail to the memory on the internet (2016)
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- Date
- 19. 1.2019 17:42:22
- Source
- Knowledge organization for a sustainable world: challenges and perspectives for cultural, scientific, and technological sharing in a connected society : proceedings of the Fourteenth International ISKO Conference 27-29 September 2016, Rio de Janeiro, Brazil / organized by International Society for Knowledge Organization (ISKO), ISKO-Brazil, São Paulo State University ; edited by José Augusto Chaves Guimarães, Suellen Oliveira Milani, Vera Dodebei
- Theme
- Internet
-
Bhatia, S.; Biyani, P.; Mitra, P.: Identifying the role of individual user messages in an online discussion and its use in thread retrieval (2016)
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- Abstract
- Online discussion forums have become a popular medium for users to discuss with and seek information from other users having similar interests. A typical discussion thread consists of a sequence of posts posted by multiple users. Each post in a thread serves a different purpose providing different types of information and, thus, may not be equally useful for all applications. Identifying the purpose and nature of each post in a discussion thread is thus an interesting research problem as it can help in improving information extraction and intelligent assistance techniques. We study the problem of classifying a given post as per its purpose in the discussion thread and employ features based on the post's content, structure of the thread, behavior of the participating users, and sentiment analysis of the post's content. We evaluate our approach on two forum data sets belonging to different genres and achieve strong classification performance. We also analyze the relative importance of different features used for the post classification task. Next, as a use case, we describe how the post class information can help in thread retrieval by incorporating this information in a state-of-the-art thread retrieval model.
- Date
- 22. 1.2016 11:50:46
- Theme
- Internet
-
Guidi, F.; Sacerdoti Coen, C.: ¬A survey on retrieval of mathematical knowledge (2015)
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- Abstract
- We present a short survey of the literature on indexing and retrieval of mathematical knowledge, with pointers to 72 papers and tentative taxonomies of both retrieval problems and recurring techniques.
- Date
- 22. 2.2017 12:51:57
-
Fluhr, C.: Crosslingual access to photo databases (2012)
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- Abstract
- This paper is about search of photos in photo databases of agencies which sell photos over the Internet. The problem is far from the behavior of photo databases managed by librarians and also far from the corpora generally used for research purposes. The descriptions use mainly single words and it is well known that it is not the best way to have a good search. This increases the problem of semantic ambiguity. This problem of semantic ambiguity is crucial for cross-language querying. On the other hand, users are not aware of documentation techniques and use generally very simple queries but want to get precise answers. This paper gives the experience gained in a 3 year use (2006-2008) of a cross-language access to several of the main international commercial photo databases. The languages used were French, English, and German.
- Date
- 17. 4.2012 14:25:22
- Source
- Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a
-
Koch, G.; Koch, W.: Aggregation and management of metadata in the context of Europeana (2017)
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- Abstract
- Mit dem In-Beziehung-Setzen und Verlinken von Daten im Internet wird der Weg zur Umsetzung des semantischen Webs geebnet. Erst die semantische Verbindung von heterogenen Datenbeständen ermöglicht übergreifende Suchvorgänge und späteres "Machine Learning". Im Artikel werden die Aktivitäten der Europäischen Digitalen Bibliothek im Bereich des Metadatenmanagements und der semantischen Verlinkung von Daten skizziert. Dabei wird einerseits ein kurzer Überblick zu aktuellen Forschungsschwerpunkten und Umsetzungsstrategien gegeben, und darüber hinaus werden einzelne Projekte und maßgeschneiderte Serviceangebote für naturhistorische Daten, regionale Kultureinrichtungen und Audiosammlungen beschrieben.
-
Layfield, C.; Azzopardi, J,; Staff, C.: Experiments with document retrieval from small text collections using Latent Semantic Analysis or term similarity with query coordination and automatic relevance feedback (2017)
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- Abstract
- One of the problems faced by users of databases containing textual documents is the difficulty in retrieving relevant results due to the diverse vocabulary used in queries and contained in relevant documents, especially when there are only a small number of relevant documents. This problem is known as the Vocabulary Gap. The PIKES team have constructed a small test collection of 331 articles extracted from a blog and a Gold Standard for 35 queries selected from the blog's search log so the results of different approaches to semantic search can be compared. So far, prior approaches include recognising Named Entities in documents and queries, and relations including temporal relations, and represent them as `semantic layers' in a retrieval system index. In this work, we take two different approaches that do not involve Named Entity Recognition. In the first approach, we process an unannotated version of the PIKES document collection using Latent Semantic Analysis and use a combination of query coordination and automatic relevance feedback with which we outperform prior work. However, this approach is highly dependent on the underlying collection, and is not necessarily scalable to massive collections. In our second approach, we use an LSA Model generated by SEMILAR from a Wikipedia dump to generate a Term Similarity Matrix (TSM). We automatically expand the queries in the PIKES test collection with related terms from the TSM and submit them to a term-by-document matrix derived by indexing the PIKES collection using the Vector Space Model. Coupled with a combination of query coordination and automatic relevance feedback we also outperform prior work with this approach. The advantage of the second approach is that it is independent of the underlying document collection.
- Date
- 10. 3.2017 13:29:57
- Series
- Information Systems and Applications, incl. Internet/Web, and HCI; 10151
- Theme
- Semantisches Umfeld in Indexierung u. Retrieval
-
Almeida Mariz, A.C.; Melo, R.O.; Almeida Mariz, T.: Challenges of organization and retrieval of photographs on social networks on the Internet (2018)
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- Theme
- Internet
-
Liu, D.-R.; Chen, Y.-H.; Shen, M.; Lu, P.-J.: Complementary QA network analysis for QA retrieval in social question-answering websites (2015)
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- Abstract
- With the ubiquity of the Internet and the rapid development of Web 2.0 technology, social question and answering (SQA) websites have become popular knowledge-sharing platforms. As the number of posted questions and answers (QAs) continues to increase rapidly, the massive amount of question-answer knowledge is causing information overload. The problem is compounded by the growing number of redundant QAs. SQA websites such as Yahoo! Answers are open platforms where users can freely ask or answer questions. Users also may wish to learn more about the information provided in an answer so they can use related keywords in the answer to search for extended, complementary information. In this article, we propose a novel approach to identify complementary QAs (CQAs) of a target QA. We define two types of complementarity: partial complementarity and extended complementarity. First, we utilize a classification-based approach to predict complementary relationships between QAs based on three measures: question similarity, answer novelty, and answer correlation. Then we construct a CQA network based on the derived complementary relationships. In addition, we introduce a CQA network analysis technique that searches the QA network to find direct and indirect CQAs of the target QA. The results of experiments conducted on the data collected from Yahoo! Answers Taiwan show that the proposed approach can more effectively identify CQAs than can the conventional similarity-based method. Case and user study results also validate the helpfulness and the effectiveness of our approach.
- Date
- 27.12.2014 19:21:29
-
Bhattacharya, S.; Yang, C.; Srinivasan, P.; Boynton, B.: Perceptions of presidential candidates' personalities in twitter (2016)
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- Abstract
- Political sentiment analysis using social media, especially Twitter, has attracted wide interest in recent years. In such research, opinions about politicians are typically divided into positive, negative, or neutral. In our research, the goal is to mine political opinion from social media at a higher resolution by assessing statements of opinion related to the personality traits of politicians; this is an angle that has not yet been considered in social media research. A second goal is to contribute a novel retrieval-based approach for tracking public perception of personality using Gough and Heilbrun's Adjective Check List (ACL) of 110 terms describing key traits. This is in contrast to the typical lexical and machine-learning approaches used in sentiment analysis. High-precision search templates developed from the ACL were run on an 18-month span of Twitter posts mentioning Obama and Romney and these retrieved more than half a million tweets. For example, the results indicated that Romney was perceived as more of an achiever and Obama was perceived as somewhat more friendly. The traits were also aggregated into 14 broad personality dimensions. For example, Obama rated far higher than Romney on the Moderation dimension and lower on the Machiavellianism dimension. The temporal variability of such perceptions was explored.
- Date
- 22. 1.2016 11:25:47
- Theme
- Internet
-
Luo, Z.; Yu, Y.; Osborne, M.; Wang, T.: Structuring tweets for improving Twitter search (2015)
0.02
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- Abstract
- Spam and wildly varying documents make searching in Twitter challenging. Most Twitter search systems generally treat a Tweet as a plain text when modeling relevance. However, a series of conventions allows users to Tweet in structural ways using a combination of different blocks of texts. These blocks include plain texts, hashtags, links, mentions, etc. Each block encodes a variety of communicative intent and the sequence of these blocks captures changing discourse. Previous work shows that exploiting the structural information can improve the structured documents (e.g., web pages) retrieval. In this study we utilize the structure of Tweets, induced by these blocks, for Twitter retrieval and Twitter opinion retrieval. For Twitter retrieval, a set of features, derived from the blocks of text and their combinations, is used into a learning-to-rank scenario. We show that structuring Tweets can achieve state-of-the-art performance. Our approach does not rely on social media features, but when we do add this additional information, performance improves significantly. For Twitter opinion retrieval, we explore the question of whether structural information derived from the body of Tweets and opinionatedness ratings of Tweets can improve performance. Experimental results show that retrieval using a novel unsupervised opinionatedness feature based on structuring Tweets achieves comparable performance with a supervised method using manually tagged Tweets. Topic-related specific structured Tweet sets are shown to help with query-dependent opinion retrieval.
- Theme
- Internet
-
Johnson, E.H.: S R Ranganathan in the Internet age (2019)
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- Abstract
- S R Ranganathan's ideas have influenced library classification since the inception of his Colon Classification in 1933. His address at Elsinore, "Library Classification Through a Century", was his grand vision of the century of progress in classification from 1876 to 1975, and looked to the future of faceted classification as the means to provide a cohesive system to organize the world's information. Fifty years later, the internet and its achievements, social ecology, and consequences present a far more complicated picture, with the library as he knew it as a very small part and the problems that he confronted now greatly exacerbated. The systematic nature of Ranganathan's canons, principles, postulates, and devices suggest that modern semantic algorithms could guide automatic subject tagging. The vision presented here is one of internet-wide faceted classification and retrieval, implemented as open, distributed facets providing unified faceted searching across all web sites.
- Theme
- Internet
-
Raieli, R.: ¬The semantic hole : enthusiasm and caution around multimedia information retrieval (2012)
0.02
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- Abstract
- This paper centres on the tools for the management of new digital documents, which are not only textual, but also visual-video, audio or multimedia in the full sense. Among the aims is to demonstrate that operating within the terms of generic Information Retrieval through textual language only is limiting, and it is instead necessary to consider ampler criteria, such as those of MultiMedia Information Retrieval, according to which, every type of digital document can be analyzed and searched by the proper elements of language for its proper nature. MMIR is presented as the organic complex of the systems of Text Retrieval, Visual Retrieval, Video Retrieval, and Audio Retrieval, each of which has an approach to information management that handles the concrete textual, visual, audio, or video content of the documents directly, here defined as content-based. In conclusion, the limits of this content-based objective access to documents is underlined. The discrepancy known as the semantic gap is that which occurs between semantic-interpretive access and content-based access. Finally, the integration of these conceptions is explained, gathering and composing the merits and the advantages of each of the approaches and of the systems to access to information.
- Date
- 22. 1.2012 13:02:10
- Footnote
- Bezugnahme auf: Enser, P.G.B.: Visual image retrieval. In: Annual review of information science and technology. 42(2008), S.3-42.
- Source
- Knowledge organization. 39(2012) no.1, S.13-22
-
Karaman, F.: Artificial intelligence enabled search engines (AIESE) and the implications (2012)
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- Abstract
- Search engines are the major means of information retrieval over the Internet. People's dependence on them increases over time as SEs introduce new and sophisticated technologies. The developments in the Artificial Intelligence (AI) will transform the current search engines Artificial Intelligence Enabled Search Engines (AIESE). Search engines already play a critical role in classifying, sorting and delivering the information over the Internet. However, as Internet's mainstream role becomes more apparent and AI technology increases the sophistication of the tools of the SEs, their roles will become much more critical. Since, the future of search engines are examined, the technological singularity concept is analyzed in detail. Second and third order indirect side effects are analyzed. A four-stage evolution-model is suggested.
- Source
- Next generation search engines: advanced models for information retrieval. Eds.: C. Jouis, u.a
-
Vechtomova, O.: Facet-based opinion retrieval from blogs (2010)
0.02
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- Abstract
- The paper presents methods of retrieving blog posts containing opinions about an entity expressed in the query. The methods use a lexicon of subjective words and phrases compiled from manually and automatically developed resources. One of the methods uses the Kullback-Leibler divergence to weight subjective words occurring near query terms in documents, another uses proximity between the occurrences of query terms and subjective words in documents, and the third combines both factors. Methods of structuring queries into facets, facet expansion using Wikipedia, and a facet-based retrieval are also investigated in this work. The methods were evaluated using the TREC 2007 and 2008 Blog track topics, and proved to be highly effective.
- Theme
- Internet
-
Azzopardi, J.; Benedetti, F.; Guerra, F.; Lupu, M.: Back to the sketch-board : integrating keyword search, semantics, and information retrieval (2017)
0.02
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- Abstract
- We reproduce recent research results combining semantic and information retrieval methods. Additionally, we expand the existing state of the art by combining the semantic representations with IR methods from the probabilistic relevance framework. We demonstrate a significant increase in performance, as measured by standard evaluation metrics.
- Series
- Information Systems and Applications, incl. Internet/Web, and HCI; 10151
-
Rorissa, A.; Yuan, X.: Visualizing and mapping the intellectual structure of information retrieval (2012)
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- Abstract
- Information retrieval is a long established subfield of library and information science. Since its inception in the early- to mid -1950s, it has grown as a result, in part, of well-regarded retrieval system evaluation exercises/campaigns, the proliferation of Web search engines, and the expansion of digital libraries. Although researchers have examined the intellectual structure and nature of the general field of library and information science, the same cannot be said about the subfield of information retrieval. We address that in this work by sketching the information retrieval intellectual landscape through visualizations of citation behaviors. Citation data for 10 years (2000-2009) were retrieved from the Web of Science and analyzed using existing visualization techniques. Our results address information retrieval's co-authorship network, highly productive authors, highly cited journals and papers, author-assigned keywords, active institutions, and the import of ideas from other disciplines.
- Date
- 29. 1.2016 19:20:01
