Diese Datenbank enthält ca. 39.000 Dokumente zu Themen aus den Bereichen Formalerschließung – Inhaltserschließung – Information Retrieval.
© 2015 W. Gödert, TH Köln, Institut für Informationswissenschaft / Powered by litecat, BIS Oldenburg (Stand: 19. Oktober 2016)
1Scharl, A. ; Hubmann-Haidvogel, A.H. ; Jones, A. ; Fischl, D. ; Kamolov, R. ; Weichselbraun, A. ; Rafelsberger, W.: Analyzing the public discourse on works of fiction : detection and visualization of emotion in online coverage about HBO's Game of Thrones.
In: Information processing and management. 52(2016) no.1, S.129-138.
Abstract: This paper presents a Web intelligence portal that captures and aggregates news and social media coverage about "Game of Thrones", an American drama television series created for the HBO television network based on George R.R. Martin's series of fantasy novels. The system collects content from the Web sites of Anglo-American news media as well as from four social media platforms: Twitter, Facebook, Google+ and YouTube. An interactive dashboard with trend charts and synchronized visual analytics components not only shows how often Game of Thrones events and characters are being mentioned by journalists and viewers, but also provides a real-time account of concepts that are being associated with the unfolding storyline and each new episode. Positive or negative sentiment is computed automatically, which sheds light on the perception of actors and new plot elements.
Inhalt: Vgl.: doi:10.1016/j.ipm.2015.02.003.
Anmerkung: Beitrag in einem Themenheft "Emotion and sentiment in social and expressive media"
Themenfeld: Schöne Literatur
2Crane, G. ; Jones, A.: Text, information, knowledge and the evolving record of humanity.
In: D-Lib magazine. 12(2006) no.3, x S.
Abstract: Consider a sentence such as "the current price of tea in China is 35 cents per pound." In a library with millions of books we might find many statements of the above form that we could capture today with relatively simple rules: rather than pursuing every variation of a statement, programs can wait, like predators at a water hole, for their informational prey to reappear in a standard linguistic pattern. We can make inferences from sentences such as "NAME1 born at NAME2 in DATE" that NAME more likely than not represents a person and NAME a place and then convert the statement into a proposition about a person born at a given place and time. The changing price of tea in China, pedestrian birth and death dates, or other basic statements may not be truth and beauty in the Phaedrus, but a digital library that could plot the prices of various commodities in different markets over time, plot the various lifetimes of individuals, or extract and classify many events would be very useful. Services such as the Syllabus Finder1 and H-Bot2 (which Dan Cohen describes elsewhere in this issue of D-Lib) represent examples of information extraction already in use. H-Bot, in particular, builds on our evolving ability to extract information from very large corpora such as the billions of web pages available through the Google API. Aside from identifying higher order statements, however, users also want to search and browse named entities: they want to read about "C. P. E. Bach" rather than his father "Johann Sebastian" or about "Cambridge, Maryland", without hearing about "Cambridge, Massachusetts", Cambridge in the UK or any of the other Cambridges scattered around the world. Named entity identification is a well-established area with an ongoing literature. The Natural Language Processing Research Group at the University of Sheffield has developed its open source Generalized Architecture for Text Engineering (GATE) for years, while IBM's Unstructured Information Analysis and Search (UIMA) is "available as open source software to provide a common foundation for industry and academia." Powerful tools are thus freely available and more demanding users can draw upon published literature to develop their own systems. Major search engines such as Google and Yahoo also integrate increasingly sophisticated tools to categorize and identify places. The software resources are rich and expanding. The reference works on which these systems depend, however, are ill-suited for historical analysis. First, simple gazetteers and similar authority lists quickly grow too big for useful information extraction. They provide us with potential entities against which to match textual references, but existing electronic reference works assume that human readers can use their knowledge of geography and of the immediate context to pick the right Boston from the Bostons in the Getty Thesaurus of Geographic Names (TGN), but, with the crucial exception of geographic location, the TGN records do not provide any machine readable clues: we cannot tell which Bostons are large or small. If we are analyzing a document published in 1818, we cannot filter out those places that did not yet exist or that had different names: "Jefferson Davis" is not the name of a parish in Louisiana (tgn,2000880) or a county in Mississippi (tgn,2001118) until after the Civil War. ; Although the Alexandria Digital Library provides far richer data than the TGN (5.9 vs. 1.3 million names), its added size lowers, rather than increases, the accuracy of most geographic name identification systems for historical documents: most of the extra 4.6 million names cover low frequency entities that rarely occur in any particular corpus. The TGN is sufficiently comprehensive to provide quite enough noise: we find place names that are used over and over (there are almost one hundred Washingtons) and semantically ambiguous (e.g., is Washington a person or a place?). Comprehensive knowledge sources emphasize recall but lower precision. We need data with which to determine which "Tribune" or "John Brown" a particular passage denotes. Secondly and paradoxically, our reference works may not be comprehensive enough. Human actors come and go over time. Organizations appear and vanish. Even places can change their names or vanish. The TGN does associate the obsolete name Siam with the nation of Thailand (tgn,1000142) - but also with towns named Siam in Iowa (tgn,2035651), Tennessee (tgn,2101519), and Ohio (tgn,2662003). Prussia appears but as a general region (tgn,7016786), with no indication when or if it was a sovereign nation. And if places do point to the same object over time, that object may have very different significance over time: in the foundational works of Western historiography, Herodotus reminds us that the great cities of the past may be small today, and the small cities of today great tomorrow (Hdt. 1.5), while Thucydides stresses that we cannot estimate the past significance of a place by its appearance today (Thuc. 1.10). In other words, we need to know the population figures for the various Washingtons in 1870 if we are analyzing documents from 1870. The foundations have been laid for reference works that provide machine actionable information about entities at particular times in history. The Alexandria Digital Library Gazetteer Content Standard8 represents a sophisticated framework with which to create such resources: places can be associated with temporal information about their foundation (e.g., Washington, DC, founded on 16 July 1790), changes in names for the same location (e.g., Saint Petersburg to Leningrad and back again), population figures at various times and similar historically contingent data. But if we have the software and the data structures, we do not yet have substantial amounts of historical content such as plentiful digital gazetteers, encyclopedias, lexica, grammars and other reference works to illustrate many periods and, even if we do, those resources may not be in a useful form: raw OCR output of a complex lexicon or gazetteer may have so many errors and have captured so little of the underlying structure that the digital resource is useless as a knowledge base. Put another way, human beings are still much better at reading and interpreting the contents of page images than machines. While people, places, and dates are probably the most important core entities, we will find a growing set of objects that we need to identify and track across collections, and each of these categories of objects will require its own knowledge sources. The following section enumerates and briefly describes some existing categories of documents that we need to mine for knowledge. This brief survey focuses on the format of print sources (e.g., highly structured textual "database" vs. unstructured text) to illustrate some of the challenges involved in converting our published knowledge into semantically annotated, machine actionable form.
Anmerkung: Vgl.: http://dlib.ukoln.ac.uk/dlib/march06/jones/03jones.html.
3Mimno, D. ; Crane, G. ; Jones, A.: Hierarchical catalog records : implementing a FRBR catalog.
In: D-Lib magazine. 11(2005) no.10, x S.
Abstract: IFLA's Functional Requirements for Bibliographic Records (FRBR) lay the foundation for a new generation of cataloging systems that recognize the difference between a particular work (e.g., Moby Dick), diverse expressions of that work (e.g., translations into German, Japanese and other languages), different versions of the same basic text (e.g., the Modern Library Classics vs. Penguin editions), and particular items (a copy of Moby Dick on the shelf). Much work has gone into finding ways to infer FRBR relationships between existing catalog records and modifying catalog interfaces to display those relationships. Relatively little work, however, has gone into exploring the creation of catalog records that are inherently based on the FRBR hierarchy of works, expressions, manifestations, and items. The Perseus Digital Library has created a new catalog that implements such a system for a small collection that includes many works with multiple versions. We have used this catalog to explore some of the implications of hierarchical catalog records for searching and browsing. Current online library catalog interfaces present many problems for searching. One commonly cited failure is the inability to find and collocate all versions of a distinct intellectual work that exist in a collection and the inability to take into account known variations in titles and personal names (Yee 2005). The IFLA Functional Requirements for Bibliographic Records (FRBR) attempts to address some of these failings by introducing the concept of multiple interrelated bibliographic entities (IFLA 1998). In particular, relationships between abstract intellectual works and the various published instances of those works are divided into a four-level hierarchy of works (such as the Aeneid), expressions (Robert Fitzgerald's translation of the Aeneid), manifestations (a particular paperback edition of Robert Fitzgerald's translation of the Aeneid), and items (my copy of a particular paperback edition of Robert Fitzgerald's translation of the Aeneid). In this formulation, each level in the hierarchy "inherits" information from the preceding level. Much of the work on FRBRized catalogs so far has focused on organizing existing records that describe individual physical books. Relatively little work has gone into rethinking what information should be in catalog records, or how the records should relate to each other. It is clear, however, that a more "native" FRBR catalog would include separate records for works, expressions, manifestations, and items. In this way, all information about a work would be centralized in one record. Records for subsequent expressions of that work would add only the information specific to each expression: Samuel Butler's translation of the Iliad does not need to repeat the fact that the work was written by Homer. This approach has certain inherent advantages for collections with many versions of the same works: new publications can be cataloged more quickly, and records can be stored and updated more efficiently.
4Jones, A.D.: Where do all the good books go? : geographic information systems and the local library.
In: Australian library journal. 42(1993) no.4, S.241-249.
Abstract: One of the problems in assessing the success of a local library in meeting the needs of a local community has been that of visualising where its readers live. The library data file listing borrowers will have as one of its items the borrower's address and in smaller communities the librarian may have some idea as to whether or not demand for the library's services were evenly distributed. In larger communities this would be more difficult. This paper describes the use of a geographic information system to use the addresses in borrower database of the Armidale City Public Library to map the spatial distribution of its borrowers. Using this technique it is possible to identify areas of high and low use.