acl acl2013 acl2013-51 knowledge-graph by maker-knowledge-mining
Source: pdf
Author: Valentin Tablan ; Kalina Bontcheva ; Ian Roberts ; Hamish Cunningham ; Marin Dimitrov
Abstract: This paper presents AnnoMarket, an open cloud-based platform which enables researchers to deploy, share, and use language processing components and resources, following the data-as-a-service and software-as-a-service paradigms. The focus is on multilingual text analysis resources and services, based on an opensource infrastructure and compliant with relevant NLP standards. We demonstrate how the AnnoMarket platform can be used to develop NLP applications with little or no programming, to index the results for enhanced browsing and search, and to evaluate performance. Utilising AnnoMarket is straightforward, since cloud infrastructural issues are dealt with by the platform, completely transparently to the user: load balancing, efficient data upload and storage, deployment on the virtual machines, security, and fault tolerance.
Reference: text
sentIndex sentText sentNum sentScore
1 uk al Abstract This paper presents AnnoMarket, an open cloud-based platform which enables researchers to deploy, share, and use language processing components and resources, following the data-as-a-service and software-as-a-service paradigms. [sent-5, score-0.335]
2 The focus is on multilingual text analysis resources and services, based on an opensource infrastructure and compliant with relevant NLP standards. [sent-6, score-0.111]
3 We demonstrate how the AnnoMarket platform can be used to develop NLP applications with little or no programming, to index the results for enhanced browsing and search, and to evaluate performance. [sent-7, score-0.308]
4 Utilising AnnoMarket is straightforward, since cloud infrastructural issues are dealt with by the platform, completely transparently to the user: load balancing, efficient data upload and storage, deployment on the virtual machines, security, and fault tolerance. [sent-8, score-0.686]
5 1 Introduction Following the Software-as-a-Service (SaaS) paradigm from cloud computing (Dikaiakos et al. [sent-9, score-0.196]
6 , 2009), a number of text processing services have been developed, e. [sent-10, score-0.271]
7 These provide information extraction services, accessible programmatically and charged per number of documents processed. [sent-13, score-0.025]
8 Secondly, the text process- ing algorithms are pre-packaged: it is not possible for researchers to extend the functional1http://www. [sent-16, score-0.031]
9 com Marin Dimitrov Ontotext AD 47A Tsarigradsko Shosse, Sofia, Bulgaria marin . [sent-20, score-0.037]
10 adapt such a service to recognise new kinds of entities). [sent-24, score-0.13]
11 Additionally, these text processing SaaS sites come with daily rate limits, in terms of number of API calls or documents that can be processed. [sent-25, score-0.025]
12 Consequently, using these services for research is not just limited in terms of text processing functionality offered, but also quickly becomes very expensive on large-scale datasets. [sent-26, score-0.318]
13 A moderately-sized collection of tweets, for example, comprises small but numerous documents, which can lead to unfeasibly high processing costs. [sent-27, score-0.024]
14 , 2009) are a type of cloud computing service which insulates developers from the low-level issues of utilising cloud infrastructures effectively, while providing facilities for efficient development, testing, and deployment of software over the Internet, following the SaaS model. [sent-29, score-0.794]
15 In the context of traditional NLP research and development, and pre-dating cloud computing, similar needs were addressed through NLP infrastructures, such as GATE (Cunningham et al. [sent-30, score-0.196]
16 These infrastructures accelerated significantly the pace of NLP research, through reusable algorithms (e. [sent-32, score-0.084]
17 rule-based pattern matching engines, machine learning algorithms), free tools for low-level NLP tasks, and support for multiple input and output document formats (e. [sent-34, score-0.058]
18 This demonstration introduces the AnnoMarket3 open, cloud-based platform, which has been developed following the PaaS paradigm. [sent-37, score-0.03]
19 It enables researchers to deploy, share, and use language processing components and resources, following the Data-as-a-Service (DaaS) and Software-as-a-Service (SaaS) paradigms. [sent-38, score-0.056]
20 It gives researchers access to an open, standard- compliant NLP infrastructure and enables them 3At the time of writing, a beta version of AnnoMarket is available at http://annomarket. [sent-39, score-0.199]
21 It supports not only NLP algorithm development and execution, but also ondemand collaborative corpus annotation and performance evaluation. [sent-43, score-0.196]
22 Important infrastructural issues are dealt with by the platform, completely transparently for the researcher: load balancing, efficient data upload and storage, deployment on the virtual machines, security, and fault tolerance. [sent-44, score-0.49]
23 In that sense, it combines the ease of use of an NLP SaaS with the openness and comprehensive facilities of the GATE NLP infrastructure. [sent-50, score-0.045]
24 Additionally, as a specialised NLP PaaS, it also supports a bring-your-own-pipeline option, which can be built easily by reusing pre-existing GATEcompatible NLP components and adding some new ones. [sent-52, score-0.048]
25 Moreover, in addition to offering entity extraction services like OpenCalais, our NLP PaaS also supports manual corpus annotation, semantic indexing and search, and performance evaluation. [sent-53, score-0.33]
26 A demonstration of running AnnoMarket multilingual NLP services on large datasets, without programming. [sent-55, score-0.338]
27 The new service deployment facilities will also be shown, including how services can optionally be shared with others. [sent-56, score-0.603]
28 A demonstration on shared research corpora via the AnnoMarket platform, following the data-as-a-service model (the sharer is responsible for ensuring no copyright violations). [sent-58, score-0.03]
29 A demonstration of the large-scale search and browsing interface, which uses the results of the NLP SaaS to offer enhanced, semantic- based functionality. [sent-60, score-0.115]
30 2 The AnnoMarket NLP PaaS This section first discusses the methodology underpinning the AnnoMarket platform, then presents its architecture and key components. [sent-61, score-0.046]
31 1 Development and Deployment Methodology The development of text analysis algorithms and pipelines typically follows a certain methodological pattern, or lifecycle. [sent-63, score-0.147]
32 It is common to use double or triple annotation, where several people perform the annotation task independently and we then measure their level of agreement (Inter-Annotator Agreement, or IAA) to quantify and control the quality of this data (Hovy, 2010). [sent-65, score-0.113]
33 The AnnoMarket platform was therefore designed to offer full methodological support for all stages of the text analysis development lifecycle: 1. [sent-66, score-0.322]
34 Create an initial prototype of the NLP pipeline, testing on a small document collection, using the desktop-based GATE user interface (Cunningham et al. [sent-67, score-0.105]
35 If required, collect a gold-standard corpus for evaluation and/or training, using the GATE Teamware collaborative corpus annotation service (Bontcheva et al. [sent-69, score-0.28]
36 Evaluate the performance of the automatic pipeline on the gold standard (either locally in the GATE development environment or on the cloud). [sent-71, score-0.063]
37 Return to step 1for further development and evaluation cycles, as needed. [sent-72, score-0.023]
38 Upload the large datasets and deploy the NLP pipeline on the AnnoMarket PaaS; 5. [sent-74, score-0.101]
39 Run the large-scale NLP experiment and download the results as XML or a standard linguistic annotation format (Ide and Romary, 2004). [sent-75, score-0.171]
40 AnnoMarket also offers scalable semantic indexing and search over the linguistic annotations and document content. [sent-76, score-0.102]
41 AnnoMarket is fully compatible with the GATE open-source architecture (Cunningham et al. [sent-79, score-0.046]
42 , 2002), in order to benefit from GATE’s numerous reusable and multilingual text processing components, and also from its infrastructural support for linguistic standards and diverse input formats. [sent-80, score-0.08]
43 2 Architecture The architecture of the AnnoMarket PaaS comprises of four layers (see Figure 1), combining 20 Figure 1: The AnnoMarket Architecture components with related capabilities. [sent-82, score-0.071]
44 The fourth, web user interface layer, contains a number of UI components that allow researchers to use the AnnoMarket platform in various ways, – – e. [sent-88, score-0.38]
45 to run an already deployed text annotation service on a large dataset, to deploy and share a new service on the platform, or to upload (and optionally share) a document collection (i. [sent-90, score-0.796]
46 There is also support for finding relevant services, deployed on the AnnoMarket platform. [sent-93, score-0.112]
47 Lastly, due to the platform running on the Amazon cloud infrastructure, there are account management interfaces, including billing information, payments, and usage reports. [sent-94, score-0.577]
48 The first vertical aspect is cloud deployment on Amazon. [sent-95, score-0.351]
49 This covers support for automatic up and down-scaling of the allocated Amazon resources, detection of and recovery from Amazon infrastructure failures and network failures, and data backup. [sent-96, score-0.134]
50 Usage monitoring and billing is the second key vertical aspect, since fine-grained pay-asyou-go ability is essential. [sent-97, score-0.086]
51 Even in the case of freely-available annotations services, Amazon usage charges are incurred and thus such functionality is needed. [sent-98, score-0.075]
52 Various usage metrics are monitored and metered so that proper billing can be guaranteed, including: storage space required by language resources and data sets; CPU utilisation ofthe annotation services; number and size ofdocuments processed. [sent-99, score-0.29]
53 In addition, we have implemented a REST programming API for AnnoMarket, so that data upload and download and running of annotation services can all be done automatically, outside of the web interface. [sent-101, score-0.616]
54 crawled web content, users’ own corpora (private or shared with others), results from running the annotation services, etc. [sent-108, score-0.15]
55 , XML, HTML, JSON, PDF, DOC), based on GATE’s comprehensive format support. [sent-111, score-0.028]
56 In all cases, when a document is being processed by AnnoMarket, the format is analysed and converted into a single unified, graph-based model of annotation: the one of the GATE NLP framework (Cunningham et al. [sent-112, score-0.063]
57 Then this internal annotation format is also used by the collaborative corpus annotation web tool, and for annotation indexing and search. [sent-114, score-0.44]
58 S3 provides a REST service for content access, as well as direct HTTP access, which provides an easy way for AnnoMarket users to upload and download content. [sent-117, score-0.36]
59 While stored on the cloud, data is protected by Amazon’s security procedures. [sent-118, score-0.056]
60 All transfers between the cloud storage, the annotation services, and the user’s computer are done via an encrypted channel, using SSL. [sent-119, score-0.309]
61 4 The Platform Layer The AnnoMarket platform provides an environment where text processing applications can be deployed as annotation services on the cloud. [sent-121, score-0.75]
62 It allows processing pipelines that were produced on a 21 Figure 2: Web-based Job Editor developer’s stand-alone computer to be deployed seamlessly on distributed hardware resources (the compute cloud) with the aim of processing large amounts of data in a timely fashion. [sent-122, score-0.25]
63 This process needs to be resilient in the face of failures at the level of the cloud infrastructure, the network com- munication, errors in the processing pipeline and in the input data. [sent-123, score-0.304]
64 The platform layer determines the optimal number of virtual machines for running a given NLP application, given the size of the document collection to be processed and taking into account the overhead in starting up new virtual machines on demand. [sent-124, score-0.628]
65 The implementation is designed to be robust in the face of hardware failures and processing errors. [sent-125, score-0.102]
66 Users can upload any pipelines compliant with the GATE Processing Resource (PR) model and these are automatically deployed as annotation services on the AnnoMarket platform. [sent-130, score-0.785]
67 5 Annotation Services As discussed above, the platform layer in AnnoMarket addresses most of the technical and methodological requirements towards the NLP PaaS, making the deployment, execution, and sharing of annotation services (i. [sent-132, score-0.807]
68 pipelines and algorithms) searcher’s a straightforward perspective, task. [sent-134, score-0.079]
69 e While the job is running, a regularly updated execution log is made available in the user’s dashboard. [sent-136, score-0.078]
70 Upon job completion, an email notification is also sent. [sent-137, score-0.041]
71 Most ofthe implementation details are hidden away from the user, who interacts with the system through a web-based job editor, depicted in Figure 2, or through a REST API. [sent-138, score-0.041]
72 The number of already deployed annotation services on the platform is growing continuously. [sent-139, score-0.75]
73 Figure 3 shows a subset of them, as well as the metadata tags associated with these services, so that users can quickly restrict which types of ser- vices they are after and then be shown only the relevant subset. [sent-140, score-0.035]
74 At the time of writing, there are services of the following kinds: • Part-of-Speech-Taggers for English, German, Dutch, -aSnpde Hungarian. [sent-141, score-0.271]
75 The deployment of new annotation services is done via a web interface (see Figure 4), where an administrator needs to configure some basic details related to the utilisation of the platform layer and provide a self-contained GATE-compatible application. [sent-150, score-1.005]
76 Platform users can only publish their own annotation services by contacting an administrator, who can validate the provided pipeline before making it publicly available to the other users. [sent-151, score-0.459]
77 This step is intended to protect the users community from malicious or poor quality pipelines. [sent-152, score-0.035]
78 3 Search and Browsing of Annotated Corpora The AnnoMarket platform also includes a service for indexing and searching over a collection of semantically annotated documents. [sent-153, score-0.469]
79 The output of an annotation service (see Figure 2) can be fed directly into a search index, which is created as the service is run on the documents. [sent-154, score-0.404]
80 This provides fa- cilities for searching over different views of document text, for example one can search the document’s words, the part-of-speech of those words, or their morphological roots. [sent-155, score-0.091]
81 As well as searching the document text, we also support searches over the documents’ semantic annotations, e. [sent-156, score-0.06]
82 Figure 5 shows a semantic search over 80,000 news web pages from the BBC. [sent-159, score-0.031]
83 They have first been pre-processed with the POS tagging, morphological analysis, and NER services on the platform and the output indexed automatically. [sent-160, score-0.525]
84 The search query is for documents, where entities of type Person are followed by any morphological form of the verb say, i. [sent-161, score-0.031]
85 4 Conclusion This paper described a cloud-based open platform for text mining, which aims to assist the development and deployment of robust, large-scale text processing applications. [sent-164, score-0.433]
86 By supporting the shar- ing of annotation pipelines, AnnoMarket also pro23 Figure 5: Example Semantic Search Results motes reuse and repeatability of experiments. [sent-165, score-0.113]
87 As the number of annotation services offered by the platform has grown, we identified a need for service search, so that users can locate useful NLP services more effectively. [sent-166, score-1.101]
88 We are currently developing a new UI, which offers search and browsing functionality, alongside various criteria, such as functionality (e. [sent-167, score-0.132]
89 POS tagger, named entity recogniser), user ratings, natural language supported). [sent-169, score-0.036]
90 A beta version is currently open to researchers for experimentation. [sent-171, score-0.084]
91 Within the next six months we plan to to solicit more shared annotation pipelines to be deployed on the platform by other researchers. [sent-172, score-0.558]
92 Gate: an architecture for development of robust hlt applications. [sent-184, score-0.069]
93 Getting more out of biomedical documents with gate’s full lifecycle open 6See http : / /www . [sent-189, score-0.117]
94 Cloud computing: Distributed internet computing for IT and scientific research. [sent-196, score-0.025]
95 Building the scientific knowledge mine (SciKnowMine): a communitydriven framework for text mining tools in direct service to biocuration. [sent-236, score-0.13]
96 In Proceedings of the ACL-02 workshop on Natural Language Processing in the biomedical domain, 7– 12 July 2002, volume 3, pages 9–13, Philadelphia, PA. [sent-248, score-0.033]
97 A distributed text mining system for online web textual data analysis. [sent-252, score-0.025]
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