439 research outputs found

    Entity Query Feature Expansion Using Knowledge Base Links

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    Recent advances in automatic entity linking and knowledge base construction have resulted in entity annotations for document and query collections. For example, annotations of entities from large general purpose knowledge bases, such as Freebase and the Google Knowledge Graph. Understanding how to leverage these entity annotations of text to improve ad hoc document retrieval is an open research area. Query expansion is a commonly used technique to improve retrieval effectiveness. Most previous query expansion approaches focus on text, mainly using unigram concepts. In this paper, we propose a new technique, called entity query feature expansion (EQFE) which enriches the query with features from entities and their links to knowledge bases, including structured attributes and text. We experiment using both explicit query entity annotations and latent entities. We evaluate our technique on TREC text collections automatically annotated with knowledge base entity links, including the Google Freebase Annotations (FACC1) data. We find that entity-based feature expansion results in significant improvements in retrieval effectiveness over state-of-the-art text expansion approaches

    Evaluating the protocol of the spectrum of hot mix asphalt mixes produced in West Virginia

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    Reviewing asphalt concrete plant-produced mixes in a laboratory setting provides further insight into pavement characteristics. Nine mix designs provided from five hot mix asphalt plant producers were evaluated throughout this research. Five mixes were Wearing I and four mixes were Base II/19 mm each of which contained various aggregate sources. First, the determination of bulk specific gravity was performed using three methods: Saturated Surface-Dry, CoreLok, and Dimensional (volumetric mass density). Moreover, assessing a mix\u27s inherent capability to be uniformly compacted is integral in both laboratory and field evaluations. The nine mix designs were assessed for uniformity following AASHTO PP 60 standard.;Furthermore, the Asphalt Mixture Performance Tester (AMPT) is a new performance testing machine that has dynamic modulus, flow number, and fatigue testing capabilities. This research focused on using the AMPT to determine dynamic modulus, fatigue characterization, and flow number values of the asphalt mixes. Master curves were developed using Mastersolver Version 2.2 to review the stiffness of the mixes. Asphalt Pavement Hierarchical Analysis Toolbox -- Fatigue Program (Alpha-FatigueTM software) was utilized to determine fatigue coefficients used to model the traditional fatigue equation. Yang Huang\u27s KENPAVE was used to develop a range of strain-modulus curves. Next, AMPT dynamic modulus values and fatigue K-value outputs were then compared using the KENPAVE strain outputs at a specified frequency level. Lastly, flow number was evaluated for rutting resistance and compared among mix designs using two methods: data smoothing method and the Francken Model

    Using Geophysics To Evaluate Levee Stability

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    Shallow slough slides have occurred along the river \side slope of Mississippi River Levees for over sixty years. Shallow slough slides also occur along smaller levees that protect tributaries of the Mississippi River. This investigation takes place along a section of the Coldwater River Levee, a tributary levee of the Mississippi River. Field observation, soil samples, and geophysical data were collected at two field sites located on the border of Tate and Tunica County, MS. The first site consists of a developed shallow slough slide that had occurred that has not yet been repaired and the second site is a potential slide area. Electromagnetic induction and electrical resistivity tomography were the geophysical methods used to define subsurface conditions that make a levee vulnerable to failure. These electrical methods are sensitive to the electrical conductivity of the soil and therefore depend upon: soil moisture, clay content, pore size distribution as well as larger scale structures at depth such as cracks and fissures. These same physical properties of the soil are also important to assessing the vulnerability of a levee to slough slides. Soil tests and field observations were also implemented in this investigation to describe and classify the soil composition of the levee material. The problem of slough slide occurrence can potentially be reduced if vulnerabilities are located with the help of geophysical techniques

    Finding Latino/a Voices in the Storytelling Process: Preservice Teachers Tell Their Stories in Digital Narratives

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    Preservice teachers in a bilingual education teacher preparation program created digital narratives that told their cultural stories within a sociocultural framework. The study revealed that the creation of digital stories within a sociocultural framework allowed preservice teachers to better understand their cultural heritages and unique places in society. This process allowed the preservice teachers to share their voices with audiences that they may have never considered before. Their newfound voices gave them the confidence to share with others about their identity and created a sense of belonging in their worlds in which they lived

    Local and global query expansion for hierarchical complex topics

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    In this work we study local and global methods for query expansion for multifaceted complex topics. We study word-based and entity-based expansion methods and extend these approaches to complex topics using fine-grained expansion on different elements of the hierarchical query structure. For a source of hierarchical complex topics we use the TREC Complex Answer Retrieval (CAR) benchmark data collection. We find that leveraging the hierarchical topic structure is needed for both local and global expansion methods to be effective. Further, the results demonstrate that entity-based expansion methods show significant gains over word-based models alone, with local feedback providing the largest improvement. The results on the CAR paragraph retrieval task demonstrate that expansion models that incorporate both the hierarchical query structure and entity-based expansion result in a greater than 20% improvement over word-based expansion approaches
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