add a test for author email extraction

The recent refactor fixed email extraction.

Thanks to Seán Healy for reporting and providing a test case.

1 files changed, 70 insertions, 0 deletions

diff --git a/tests/files/document/author_email.tei.xml b/tests/files/document/author_email.tei.xml
new file mode 100644
index 0000000..f342fac
--- /dev/null
+++ b/tests/files/document/author_email.tei.xml
@@ -0,0 +1,70 @@
+<?xml version="1.0" encoding="UTF-8"?>
+<TEI xml:space="preserve" xmlns="http://www.tei-c.org/ns/1.0" 
+xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" 
+xsi:schemaLocation="http://www.tei-c.org/ns/1.0 https://raw.githubusercontent.com/kermitt2/grobid/master/grobid-home/schemas/xsd/Grobid.xsd"
+ xmlns:xlink="http://www.w3.org/1999/xlink">
+	<teiHeader xml:lang="en">
+		<fileDesc>
+			<titleStmt>
+				<title level="a" type="main">Task-Based Intelligent Retrieval and Recommendation</title>
+			</titleStmt>
+			<publicationStmt>
+				<publisher/>
+				<availability status="unknown"><licence/></availability>
+			</publicationStmt>
+			<sourceDesc>
+				<biblStruct>
+					<analytic>
+						<author role="corresp">
+							<persName><forename type="first">Chirag</forename><surname>Shah</surname></persName>
+							<email>redacted@example.com</email>
+							<affiliation key="aff0">
+								<orgName type="institution">University of Washington</orgName>
+								<address>
+									<settlement>Seattle</settlement>
+									<country key="US">USA</country>
+								</address>
+							</affiliation>
+						</author>
+						<title level="a" type="main">Task-Based Intelligent Retrieval and Recommendation</title>
+					</analytic>
+					<monogr>
+						<imprint>
+							<date/>
+						</imprint>
+					</monogr>
+					<idno type="MD5">6C18173427FE3FAD756BB2F4F7665855</idno>
+				</biblStruct>
+			</sourceDesc>
+		</fileDesc>
+		<encodingDesc>
+			<appInfo>
+				<application version="0.7.1-SNAPSHOT" ident="GROBID" when="2021-11-02T09:03+0000">
+					<desc>GROBID - A machine learning software for extracting information from scholarly documents</desc>
+					<ref target="https://github.com/kermitt2/grobid"/>
+				</application>
+			</appInfo>
+		</encodingDesc>
+		<profileDesc>
+			<textClass>
+				<keywords>
+					<term>Task-based IR</term>
+					<term>Recommendation systems</term>
+					<term>Information Fostering</term>
+				</keywords>
+			</textClass>
+			<abstract>
+<div xmlns="http://www.tei-c.org/ns/1.0"><p>While the act of looking for information happens within a context of a task from the user side, most search and recommendation systems focus on user actions ('what'), ignoring the nature of the task that covers the process ('how') and user intent ('why'). For long, scholars have argued that IR systems should help users accomplish their tasks and not just fulfill a search request. But just as keywords have been good enough approximators for information need, satisfying a set of search requests has been deemed to be good enough to address the task. However, with changing user behaviors and search modalities, specifically found in conversational interfaces, the challenge and opportunity to focus on task have become critically important and central to IR. In this talk, I will discuss some of the key ideas and recent worksboth theoretical and empirical to study and support aspects of task. I will show how we could derive user's search path or strategy and intentions, and how they could be instrumental in not only creating more personalized search and recommendation solutions, but also solving problems not possible otherwise. Finally, I will extend this to the realm of intelligent assistants with our recent work in a new area called Information Fostering, where our knowledge of the user and the task can help us address another classical problem in IRpeople don't know what they don't know.</p></div>
+			</abstract>
+		</profileDesc>
+	</teiHeader>
+	<text xml:lang="en">
+		<body/>
+		<back>
+			<div type="references">
+
+				<listBibl/>
+			</div>
+		</back>
+	</text>
+</TEI>