We present a keyphrase extraction algorithm for scientific publications. Different from previous work, we introduce features that capture the positions of phrases in document with respect to logical sections found in scientific discourse. We also introduce features that capture salient morphological phenomena found in scientific keyphrases, such as whether a candidate keyphrase is an acronyms or uses specific terminologically productive suffixes. We have implemented these features on top of a baseline feature set used by Kea [1]. In our evaluation using a corpus of 120 scientific publications multiply annotated for keyphrases, our system significantly outperformed Kea at the p < .05 level. As we know of no other existing multiply annotated keyphrase document collections, we have also made our evaluation corpus publicly available. We hope that this contribution will spur future comparative research.
Scholarly digital libraries increasingly provide analytics to information within documents themselves. This includes information about the logical document structure of use to downstream components, such as search, navigation and summarization. We describe SectLabel, a module that further develops existing software to detect the logical structure of a document from existing PDF files, using the formalism of conditional random fields. While previous work has assumed access only to the raw text representation of the document, a key aspect of our work is to integrate the use of a richer representation of the document that includes features from optical character recognition (OCR), such as font size and text position. Our experiments reveal that using such rich features improves logical structure detection by a significant 9 F 1 points, over a suitable baseline, motivating the use of richer document representations in other digital library applications.
Purpose
– The purpose of this study is to measure intellectual capital of the firm through the eyes of the consumer by investigating the relationships between financial-based brand equity (FBBE) and consumer-based brand equity (CBBE) and their related constructs.
Design/methodology/approach
– Fifteen consumer brands were evaluated based on three different perspectives of CBBE, and were then regressed on FBBE. Prior to the regression analysis, the FBBEs of 15 consumer brands were standardized using the total assets and three-year weighted average of their brand equity values.
Findings
– Findings show that existing CBBE scales and related brand dimensions partially explain FBBE, namely, sustainability and brand experience, and that the product category contributes significantly in explaining FBBE. In addition, brand experience is positively associated with FBBE.
Research limitations/implications
– The study only includes brands from the food, electronics and clothing industries.
Practical implications
– The study provides guidance to brand managers regarding which brand dimensions directly influence brands’ financial values.
Originality/value
– The paper empirically measures consumers’ perceptions of the firm’s intellectual capital by using brand equity.
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