FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W18725020> ?p ?o ?g. }

• W18725020 abstract "Searching for scientific publications is a tedious task, especially when exploring an unfamiliar domain.Typical scholarly search engines produce lengthy unstructured result lists, which are difficult to comprehend, interpret and browse.An informative visual summary could convey useful information about the returned results as a whole, without the need to sift through individual publications.The first contribution of this thesis is a novel method of representing academic search results with concise and informative topic maps.The method consists of two steps: i) extracting interrelated topics from the publication titles and abstracts, and ii) summarizing the resulting topic graph. In the first step we map the returned publications to articles and categories of Wikipedia, constructing a graph of relevant topics with hierarchical relations. In the second step we sequentially build a summary of the topic graph that represents the search results in the most informative way. We rely on sequential prediction to automatically learn to build informative summaries from examples. The summarized topic maps share the most of the benefits and avoid most of the drawbacks of the current methods for grouping documents, such as clustering, topic models, and predefined taxonomies.Specifically, the topic maps are dynamic, fine-grained, of flexible granularity, with up-to-date topics connected with informative relations and having meaningful concise labels.The second contribution of this thesis is a method for bootstrapping domain-specific ontologies from the categories of Wikipedia. The method performs three steps: i) selecting the set of categories relevant to the domain, ii) classifying the categories into classes and individuals, and iii) classifying the sub-category relations into ``subclass-of'', ``instance-of'', ``part-of'' and ``related-to''.In each step we rely on binary classification, which makes the method flexible and easily extensible with new features.For the purpose of academic search, the proposed method advances the creation of semantically rich topic maps.In general, the method semi-automates the construction of large-scale domain ontologies, benefiting multiple potential applications. Providing ground truth data for structured prediction of large objects, such as topic map summaries or domain ontologies, is tedious. The last contribution of this thesis is an initial investigation into reducing the labeling effort in structured prediction tasks.First, we present a labeling interface that suggests topics to be added to the ground truth topic map summary.We modify a state of the art sequential prediction method to iteratively learn from the summaries one topic at a time, while retaining the convergence guarantees. Second, we present an interactive learning method for selecting the categories of Wikipedia relevant to a given domain.The method reduces the number of required labels by actively selecting the queries to the annotator and learning one label at a time." @default.
• W18725020 created "2016-06-24" @default.
• W18725020 creator A5088922075 @default.
• W18725020 date "2015-02-23" @default.
• W18725020 modified "2023-10-01" @default.
• W18725020 title "Towards structured representation of academic search results" @default.
• W18725020 cites W112666333 @default.
• W18725020 cites W1503428008 @default.
• W18725020 cites W1521626219 @default.
• W18725020 cites W1529522905 @default.
• W18725020 cites W1530746484 @default.
• W18725020 cites W1533168581 @default.
• W18725020 cites W1552847225 @default.
• W18725020 cites W1555805532 @default.
• W18725020 cites W1561887350 @default.
• W18725020 cites W1569531029 @default.
• W18725020 cites W1572864191 @default.
• W18725020 cites W1594105789 @default.
• W18725020 cites W1647729745 @default.
• W18725020 cites W1802555571 @default.
• W18725020 cites W1846286066 @default.
• W18725020 cites W1880262756 @default.
• W18725020 cites W190289764 @default.
• W18725020 cites W1965893683 @default.
• W18725020 cites W1970043789 @default.
• W18725020 cites W1980995378 @default.
• W18725020 cites W1987605949 @default.
• W18725020 cites W1996764654 @default.
• W18725020 cites W1998084297 @default.
• W18725020 cites W2001082470 @default.
• W18725020 cites W2001914359 @default.
• W18725020 cites W2031046392 @default.
• W18725020 cites W2031248101 @default.
• W18725020 cites W2032327522 @default.
• W18725020 cites W2035720976 @default.
• W18725020 cites W2036399631 @default.
• W18725020 cites W2037802158 @default.
• W18725020 cites W2038663599 @default.
• W18725020 cites W203883998 @default.
• W18725020 cites W2038890640 @default.
• W18725020 cites W2064153289 @default.
• W18725020 cites W2066680326 @default.
• W18725020 cites W2066760136 @default.
• W18725020 cites W2072644219 @default.
• W18725020 cites W2074449313 @default.
• W18725020 cites W2078726879 @default.
• W18725020 cites W2078790410 @default.
• W18725020 cites W2080493390 @default.
• W18725020 cites W2081580037 @default.
• W18725020 cites W2090288396 @default.
• W18725020 cites W2091273188 @default.
• W18725020 cites W2095478124 @default.
• W18725020 cites W2096876410 @default.
• W18725020 cites W2098062695 @default.
• W18725020 cites W2100341149 @default.
• W18725020 cites W2104583100 @default.
• W18725020 cites W2105842272 @default.
• W18725020 cites W2106490775 @default.
• W18725020 cites W2109819069 @default.
• W18725020 cites W2110920860 @default.
• W18725020 cites W2111313508 @default.
• W18725020 cites W2112648537 @default.
• W18725020 cites W2117154949 @default.
• W18725020 cites W2117763124 @default.
• W18725020 cites W2118585731 @default.
• W18725020 cites W2120946550 @default.
• W18725020 cites W2121996546 @default.
• W18725020 cites W2122865749 @default.
• W18725020 cites W2123142779 @default.
• W18725020 cites W2126355364 @default.
• W18725020 cites W2126536832 @default.
• W18725020 cites W2129022247 @default.
• W18725020 cites W2132827946 @default.
• W18725020 cites W2134804405 @default.
• W18725020 cites W2136480620 @default.
• W18725020 cites W2139653758 @default.
• W18725020 cites W2140124448 @default.
• W18725020 cites W2142313532 @default.
• W18725020 cites W2143930661 @default.
• W18725020 cites W2145630740 @default.
• W18725020 cites W2147107544 @default.
• W18725020 cites W2149029960 @default.
• W18725020 cites W2150286230 @default.
• W18725020 cites W2152588577 @default.
• W18725020 cites W2154785834 @default.
• W18725020 cites W2156909104 @default.
• W18725020 cites W2157791002 @default.
• W18725020 cites W2165636119 @default.
• W18725020 cites W2171040110 @default.
• W18725020 cites W2259172389 @default.
• W18725020 cites W2400777513 @default.
• W18725020 cites W2510089130 @default.
• W18725020 cites W2613678961 @default.
• W18725020 cites W2914331073 @default.
• W18725020 cites W2949600092 @default.
• W18725020 cites W2962957031 @default.
• W18725020 cites W89857650 @default.
• W18725020 cites W2010624529 @default.
• W18725020 cites W2997181101 @default.
• W18725020 cites W90362830 @default.

• next