Support Vector Machine (SVM)

Overview

SVM^light is an implementation of Support Vector Machines (SVMs) in C. The main features of the program are the following:

• fast optimization algorithm
  • working set selection based on steepest feasible descent
  • “shrinking” heuristic
  • caching of kernel evaluations
  • use of folding in the linear case
• solves classification and regression problems. For multivariate and structured outputs use SVM^struct.
• solves ranking problems (e. g. learning retrieval functions in STRIVER search engine).
• computes XiAlpha-estimates of the error rate, the precision, and the recall
• efficiently computes Leave-One-Out estimates of the error rate, the precision, and the recall
• includes algorithm for approximately training large transductive SVMs (TSVMs) (see also Spectral Graph Transducer)
• can train SVMs with cost models and example dependent costs
• allows restarts from specified vector of dual variables
• handles many thousands of support vectors
• handles several hundred-thousands of training examples
• supports standard kernel functions and lets you define your own
• uses sparse vector representation

Description

SVM^light is an implementation of Vapnik’s Support Vector Machine [Vapnik, 1995] for the problem of pattern recognition, for the problem of regression, and for the problem of learning a ranking function. The optimization algorithms used in SVM^light are described in [Joachims, 2002a ]. [Joachims, 1999a]. The algorithm has scalable memory requirements and can handle problems with many thousands of support vectors efficiently.

The software also provides methods for assessing the generalization performance efficiently. It includes two efficient estimation methods for both error rate and precision/recall. XiAlpha-estimates [Joachims, 2002a, Joachims, 2000b] can be computed at essentially no computational expense, but they are conservatively biased. Almost unbiased estimates provides leave-one-out testing. SVM^light exploits that the results of most leave-one-outs (often more than 99%) are predetermined and need not be computed [Joachims, 2002a].

New in this version is an algorithm for learning ranking functions [Joachims, 2002c]. The goal is to learn a function from preference examples, so that it orders a new set of objects as accurately as possible. Such ranking problems naturally occur in applications like search engines and recommender systems.

Futhermore, this version includes an algorithm for training large-scale transductive SVMs. The algorithm proceeds by solving a sequence of optimization problems lower-bounding the solution using a form of local search. A detailed description of the algorithm can be found in [Joachims, 1999c]. A similar transductive learner, which can be thought of as a transductive version of k-Nearest Neighbor is the Spectral Graph Transducer.

SVM^light can also train SVMs with cost models (see [Morik et al., 1999]).

The code has been used on a large range of problems, including text classification [Joachims, 1999c][Joachims, 1998a], image recognition tasks, bioinformatics and medical applications. Many tasks have the property of sparse instance vectors. This implementation makes use of this property which leads to a very compact and efficient representation.

Other SVM Resources

• GMD-First Berlin
• Kernel-Machines Web Site
• Bell Labs
• Microsoft Research
• Royal Holloway College
• ANU Canberra
• MIT
• Bristol CI-Group

source: http://svmlight.joachims.org/

Resources of Text Categorization

On Line Papers

• Overview and Feature selection
  1. David Dolan Lewis, Representation and Learning in Information Retrieval. PhD thesis, Department of Computer Science; Univ. of Massachusetts; Amherst, MA 01003, 1992.
  2. Yiming Yang and Xin Liu A re-examination of text categorization methods. Proceedings of ACM SIGIR Conference on Research and Development in Information Retrieval, (SIGIR), 1999.
  3. Yang, Y., Pedersen J.P. A Comparative Study on Feature Selection in Text Categorization Proceedings of the Fourteenth International Conference on Machine Learning (ICML’97), 1997.
• Support Vector Machines
  1. Thorsten Joachims , Text Categorization with Support Vector Machines: Learning with Many Relevant Features. European Conference on Machine Learning (ECML), Claire Nédellec and Céline Rouveirol (ed.), 1998.
  2. Robert Cooley , Classification of News Stories Using Support Vector Machines (1999). Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence Text Mining Workshop, August 1999.
  3. kernel-machines.org.
  4. S. Dumais and H. Chen, Hierarchical classification of Web content. Proceedings of SIGIR’00, August 2000, pp. 256-263.
• Naive Bayes
  1. Andrew McCallum and Kamal Nigam, A Comparison of Event Models for Naive Bayes Text Classification. AAAI-98 Workshop on “Learning for Text Categorization”
• K Nearest Neighbor
  1. Jerome H. Friedman , J. H. “Flexible Metric Nearest Neighbor Classification.” Technical Report (Nov. 1994).
• Decision Tree
  1. C. Apte ,F. Damerau, and S.M. Weiss, Text Mining with Decision Trees and Decision Rules, in Conference on Automated Learning and Discovery, Carnegie-Mellon University, June 1998.
  2. C. Apte , F. Damerau, and S.M. Weiss, Towards Language Independent Automated Learning of Text Categorization Models, in ACM SIGIR’94, July 1994.
  3. Robert E. Schapire and Yoram Singer, BoosTexter: A boosting-based system for text categorization. Machine Learning, to appear.
• Neural Network
• New Event Detection or Topic Detection
  1. J. Allan , J. Carbonell, G. Doddington, J. Yamron, and Y. Yang, “Topic Detection and Tracking Pilot Study: Final Report”. Proceedings of the DARPA Broadcast News Transcription and Understanding Workshop, pp. 194-218. (April 1998)
  2. J. Allan , R. Papka, and V. Lavrenko, “On-line New Event Detection and Tracking”, in SIGIR ‘98. (April 1998)
  3. Chris Clifton, Robert Cooley , TopCat: Data Mining for Topic Identification in a Text Corpus (1999). Proceedings of the 3rd European Conference of Principles and Practice of Knowledge Discovery in Databases, 1999.
• Hierarchical Categorization
  1. Doug Baker, Thomas Hofmann, Andrew McCallum and Yiming Yang, A Hierarchical Probabilistic Model for Novelty Detection in Text. Submitted to NIPS’99.
  2. Kamal Nigam, John Lafferty, Andrew McCallum , Using Maximum Entropy for Text Classification. IJCAI’99 Workshop on Information Filtering.
  3. Soumen Chakrabarti , Byron Dom, Rakesh Agrawal, and Prabhakar Raghavan, Scalable feature selection, classification and signature generation for organizing large text databases into hierarchical topic taxonomies. International Journal on Very Large Data Bases, 7(3) pp163-178. Invited paper.
  4. K. Wang , S. Zhou, S.C. Liew, “Building hierarchical classifiers using class proximity”, VLDB 1999, September 1999, Edinburgh, UK, Morgan Kaufmann, 363-374.
  5. D. Koller and M. Sahami, Hierarchically classifying documents using very few words, . Proceedings of the 14th International Conference on Machine Learning (ICML), Nashville, Tennessee, July 1997, pages 170–178.

Machine Learning Resources

• David Aha’s list of machine learning resources

On Line Softwares

• SVM_LIGHT,By Thorsten JoachimsSupport Vector Machine
• Bow: A Toolkit for Statistical Language Modeling, Text Retrieval, Classification and Clustering, by Andrew McCallum. Naive Bayes approach
• K Nearest Neighbour Classifier, by CMU
• BAYDA 1.31 – Bayesian Predictive Discriminant Analysis, by Complex Systems Computation Group, Department of Computer Science, University of Helsinki

source:http://www.cs.helsinki.fi/group/doremi/categorization/categorylinks.html

Solidaritas untuk Sesama (Donate for Charity)

Assalammua’alaikum wr.wb,..

Semoga kita semua selalu berada dalam lindugan dan Rahmat Nya. Amin,..

Terkait dengan kondisi saudara kita Pak Triyono (dosen TIF FST UIN),  beliau saat ini sangat memerlukan bantuan dan uluran tangan kita.

Saat ini, beliau setiap 2 atau 3x dalam seminggu melakukan cuci darah dan dibiayai oleh pihak kampus. Namun dalam waktu dekat, pembiayaan tsb akan dihentikan karena sebab tertentu. Salah satu alternatif solusi jangka panjang untuk mengatasi masalah beliau tresebut adalah beliau akan melakukan transplantasi ginjal.

Dari info yg saya dapat dan juga setelah berbincang dengan secara langsung dengan beliau, beliau belum mempunyai kemampuan untuk melaksanakan “Transpalnatasi Ginjal”. Biaya operasi tsb berkisar Rp. 150 juta atau RM. 60,000.

Untuk itu, saya mengajak diri sendiri dan kawan2 semua untuk sama2 peduli terhadap salah satu saudara kita ini. Mudah2an kita diberi kemudahan dan kesanggupan untuk berbuat amal kebaikan. Amin

Uluran tangan dan dan bantuan kita akan sangat berarti jika segera direalisasikan.

Salam setia kawan,..

Ness
Penyampai berita

bantuan dapat di alamatkan ke nomor rekening :

Triyono : 0118-0067454522 Bumiputra Commerce Bank (CIMB) Malaysia,

4450403445 Rekening BCA Cabang Katamso, Yogyakarta :

related news:

A letter to everybody

http://trionolita. blogspot. com/
August, 2008.

Dear all,

Assalaamu’alaikum wr.wb.

My name is Lita Rahmasari, 28 years old. I’m a housewife. My husband’s name is Triyono, 33 years. We are from Indonesia and have married for 5 years. My husband is studying in UTM Malaysia under an RSG scheme.

He started study for Master Degree UTM in December 2005 with normal health condition. He did the study normally in fist semester and got the good result, with GPA 3.86. In second semester, August 2006, my husband got both of his kidney failure, so he postponed his study and went back to Indonesia for haemodialysis. Due to our financial condition, the government facilitated us with limited fund to pay the kidney treatments. It was not enough to keep my husband in a good condition, because it could only cover the basic service for kidney treatment, 2 times a week of dialysis and blood transfusion whenever hemoglobin (Hb, the amount of good-quality red-blood cells) was very low.

In January 2007, he decided to continue his study and back to UTM. He could continue but still need to dialysis for three times a week at UTM medical center and medical check-up every three month at Hospital Sultanah Aminah Johor Bahru. He is now in better condition. Alhamdulillah, UTM had pay for the cost of dialysis about RM3,000.00 for a month till now. He just finished his Master Degree at June 2008.

Now, he just started his PhD Degree on July 2008. His Supervisor told him that UTM can’t pay the cost for his dialysis anymore for next semester, January 2009. He must pay the dialysis by himself or do kidney transplantation. So, he wants to do kidney transplantation for better quality of life, because dialysis is considered very hard: costly, painful, takes time, and physically weakening. He wants to do the kidney transplantation as soon as possible, before the end of this year. His mother is generously willing to donate her kidney. We already asked to head of Renal Treatment at Sardjito Provincial Hospital (Prof. dr. Syahbani), kidney transplantation cost is about RM60,000,00. It is very hard for us to take, because currently my husband doesn’t have a permanent job.

We desperately need financial support for the kidney transplantation. It is urgent to do the kidney transplantation, for the sake of my husband’s life. Without the transplant, his living opportunity would be very low. Our expectation is to be able to live normally without routine dialysis.

Thank you for your attention and I pray to Allah that everything will be ok and run smoothly. Thank you.

Wassalaamu’alaikum wr.wb.

Lita Rahmasari
Phone: +(60) 167933004

Berikut beberapa sumber berkaitan dengan Text Analysis dan Content Analysis Program

sumber  (source): http://academic.csuohio.edu/kneuendorf/content/cpuca/qtap.htm

:

Quantitative Text Analysis Programs

CATPAC (http://www.terraresearch.com/) CATPAC reads text files and produces a variety of outputs ranging from simple diagnostics (e.g., word and alphabetical frequencies) to a summary of the “main ideas” in a text. It uncovers patterns of word usage and produces such outputs as simple word counts, cluster analysis (with icicle plots), and interactive neural cluster analysis. A nifty add-on program called Thought View can generate two and three-dimensional concept maps based on the results of CATPAC analyses (one especially neat feature of Thought View allows users to look at the results through 3-D glasses and experience MDS-style output like never before, in true, movie theater-style, 3-D fashion!).

Computer Programs for Text Analysis (http://unix.dsu.edu/~johnsone/ericpgms.html) This is not a single computer program but rather a series of separate programs by Eric Johnson that each perform one or two basic functions, including analyzing appearances of characters in a play (ACTORS program), getting KWIC (CONCORD program), computing the amount of quotation in texts (DIALOG program), and comparing the vocabulary of two texts (IDENT program). The programs seem ideal for literary-type analyses.

Concordance 2.0 (http://www.rjcw.freeserve.co.uk/) This program lets you make full concordances to texts of any size, limited only by available disk space and memory.  You can also make fast concordances, picking your selection of words from text, and make Web Concordances: turn your concordance into linked HTML files, ready for publishing on theWeb, with a single click. See the original Web Concordances for examples.

Diction 5.0 (http://www.sagepub.com/) Diction 5.0 contains a series of built-in dictionaries that search text documents for 5 main semantic features (Activity, Optimism, Certainty, Realism and Commonality) and 35 sub-features (including tenacity, blame, ambivalence, motion, and communication). After the user’s text is analyzed, Diction compares the results for each of the 40 dictionary categories to a “normal range of scores” determined by running more than 20,000 texts through the program. Users can compare their text to either a general normative profile of all 20,000-plus texts OR to any of 6 specific sub-categories of texts (business, daily life, entertainment, journalism, literature, politics, scholarship) that can be further divided into 36 distinct types (e.g., financial reports, computer chat lines, music lyrics, newspaper editorials, novels and short stories, political debates, social science scholarship). In addition, Diction outputs raw frequencies (in alphabetical order), percentages, and standardized scores; custom dictionaries can be created for additional analyses.

DIMAP (http://www.clres.com/) DIMAP stands for DIctionary MAintenance Programs, and its primary purpose is dictionary development. The program includes a variety of tools for lexicon building rooted in computational linguistics and natural language processing (Litkowski, 1992). With DIMAP, users can build, manage, edit, maintain, search and compare custom and established dictionaries. The program also includes a text analysis module called MCCA (the lite version of which is described below).

General Inquirer (Internet version) (http://www.wjh.harvard.edu/~inquirer/) This venerable, still widely-used program has found new life on the World Wide Web. The online version of the General Inquirer gets our vote for the simplest and quickest way to do a computer text analysis–simply visit the Internet General Inquirer site, type or paste some text into a box, click submit, and your text will be analyzed. The Internet General Inquirer codes and classifies text using the Harvard IV-4 dictionary, which assess such features as valence, Osgood’s three semantic dimensions, language reflecting particular institutions, emotion-laden words, cognitive orientation, and more. The program also returns cumulative statistics (e.g., simple frequencies for words appearing in the text) at the end of each analysis. Though we could not find any information on a software-based version of the Inquirer, creator Phillip J. Stone holds summer seminars on the program at the University of Essex.

HAMLET (http://www.apb.cwc.net/homepage.htm) “The main idea of HAMLET © is to search a text file for words in a given vocabulary list, and to count joint frequencies within any specified context unit, or as collocations within a given span of words.  Individual word frequencies (fi) , joint frequencies (fij) for pairs of words (i,j), both expressed in terms of the chosen unit of context, and the corresponding standardised joint frequencies are displayed in a similarities matrix, which can be submitted to a simple cluster analysis and multi-dimensional scaling.  A further option allows comparison of the results of applying multi- dimensional scaling to matrices of joint frequencies derived from a number of texts, using Procrustean Individual Differences Scaling (PINDIS).”

INTEXT/TextQuest–Text Analysis Software (http://www.intext.de) INTEXT is a program designed for the analysis of texts in the humanities and the social sciences. It performs text analysis, indexing, concordance, KWIC, KWOC, readability analysis, personality structure analysis, word lists, word sequence, word permutation, stylistics, and more.  TextQuest is the Windows version of INTEXT.  It performs all of the INTEXT analyses, but through an easier-to-use Windows interface.

Lexa (http://nora.hd.uib.no/lexainf.html) Designed with linguists in mind, Lexa Corpus Processing Software is a suite of programs for tagging, lemmatization, type/token frequency counts, and several other computer text analysis functions.

LIWC (Lingustic Inquiry and Word Count software) (https://www.erlbaum.com/shop/tek9.asp?pg=products&specific=1-56321-208-0) LIWC has a series of 68 built-in dictionaries that search text files and calculate how often the words match each of the 68 pre-set dimensions (dictionaries), which include linguistic dimensions, word categories tapping psychological constructs, and personal concern categories. The program also allows users to create custom dictionaries. The program seems especially useful to psychologists who wish to examine patient narratives.

MCCA Lite (http://www.clres.com/) Though somewhat hampered by quirks such as limited function availability, the lite version of MCCA analyzes text by producing frequencies, alphabetical lists, KWIC, and coding with built-in dictionaries. The built-in dictionaries search for textual dimensions such as activity, slang, and humor expression. The program’s window-driven output makes sorting and switching between results easy. MCCA also includes a multiple-person transcript analysis function suitable for examining plays, focus groups, interviews, hearings, TV scripts, other such texts.

MECA (no website) MECA, which stands for Map Extraction Comparison and Analysis, contains 15 routines for text analysis. Many of these routines are for doing cognitive mapping and focus on both concepts and the relations between them. There are also routines for doing more classic content analyses, including a multi-unit data file output routine that shows the number of times each concept appears in each map.

MonoConc (http://www.ruf.rice.edu/~barlow/mono.html) As the name suggests, MonoConc primarily produces concordance information. These results can be sorted and displayed in several different user-configurable ways. The program also produces frequency and alphabetical information about the words in a given corpus.

ParaConc (http://www.ruf.rice.edu/~barlow/parac.html) ParaConc is a bilingual/multilingual concordance program designed to be used for contrastive corpus-based language research. For Macintosh, Windows version announced.

PCAD 2000 (http://www.gb-software.com/) PCAD 2000 applies the Gottschalk-Gleser content analysis scales (which measure the magnitude of clearly defined and categorized mental or emotional states) to transcriptions of speech samples and other machine-readable texts. In addition to deriving scores on a variety of scales, including anxiety, hostility, social alienation, cognitive impairment, hope, and depression, the program compares scores on each scale to norms for the demographic groups of subjects. It can also explain the significance and clinical implications of scores and place subjects into clinical diagnostic classifications derived from the Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition (DSM-IV), developed by the American Psychiatric Association.

PROTAN (site down) PROTAN (for PROTocol ANalyzer) is a computer-aided content analysis system.  It addresses the question of how does the text look like.  To achieve this first task, PROTAN rests on a series of semantic dictionaries that are part of the system.  The second task to which PROTAN is tuned is to answer the question of what the text is talking about. What are the main themes in it?  For more:  http://www.psp.ucl.ac.be/~upso/protan/PROTANAE.html

SALT (Systematic Analysis of Language Transcripts) (http://www.waisman.wisc.edu/salt/index.htm) This program is designed mainly to help clinicians identify and document specific language problems. It executes a myriad of analyses, including types of utterances (e.g., incomplete, unintelligible, nonverbal), mean length of utterances, number and length of pauses and rate of speaking, and frequencies for sets of word (e.g., negatives, conjunctions, and custom dictionaries). The Salt Reference Database, described online, allows users to compare the results of their SALT analyses to normative language measures collected via a sample of more than 250 children of various ages, economic backgrounds, and abilities in the Madison, Wisconsin area.

SWIFT Content Analysis Software (site down) SWIFT stands for Structured Word Identification and Frequency Table, an interactive, keyword-based program for analyzing multiple, short texts. SWIFT is free, operating system DOS.  This free program seems best suited to coding open ended text responses.

TABARI (Text Analysis By Augmented Replacement Instructions) (http://www.ku.edu/~keds/software.dir/tabari.html) The successor to KEDS, this program is specifically designed for analyzing short news stories, such as those found in wire service reports. It codes international event data (which are essentially codes recording the interactions between actors) using pattern recognition and simple grammatical parsing. The authors have developed a number of dictionaries to help code event data. The WEIS coding scheme, for example, can determine who acts against whom, as in the case of an Iraqi attack against Kuwait. When such an event is reported in a news story, the program can automatically code the aggressor, victim and action, as well as the date of the event. TABARI is currently only available for Macintosh, but a Windows version is in the works.

TextAnalyst (http://www.megaputer.com/index.php3) TextAnalyst is an intelligent text mining and semantic information search system.  TextAnalyst implements a unique neural network technology for structural processing of texts written in natural language. This technology automates the work with large volumes of textual information and can be applied effectively to perform the following tasks:  creation of knowledge bases expressed in a natural language, as well as creation of hypertext, searchable, and expert systems; AND automated indexing, topic assignment, and abstracting of texts.

TEXTPACK 7.0 (http://www.social-science-gesis.de/en/software/textpack/index.htm) The TEXTPACK program, which was originally designed for the analysis of open-ended survey responses, has been broadened in recent years to include features of use to content, literary and linguistic analysts. It now produces word frequencies, alphabetical lists, KWIC and KWOC (KeyWord Out of Context) searches, cross references, word comparisons between two texts, and coding according to user-created dictionaries. This multi-unit data file output can be imported in statistical analysis software. The new Windows version of the program takes full advantage of the Windows user interface.

TextSmart by SPSS Inc. (http://www.spss.com/spssbi/textsmart/) This software, designed primarily for the analysis of open-ended survey responses, uses cluster analysis and multidimensional scaling techniques to automatically analyze key words and group texts into categories. Thus, it can “code” without the use of a user-created dictionary. TextSmart has a pleasant, easy-to-use Windows interface that allows for quick sorting of words into frequency and alphabetical lists. It also produces colorful, rich-looking graphics like bar charts and two-dimensional MDS plots.

Tropes (http://www.semantic-knowledge.com/) “Designed for Semantic Classification, Keyword Extraction, Linguistic and Qualitative Analysis, Tropes software is a perfect tool for Information Science, Market Research, Sociological Analysis, Scientific and Medical studies, and more..”

VBPro (http://mmmiller.com/vbpro/vbpro.htm) Outputs frequency and alphabetical word lists, key words in context (KWIC), and coded strings of word-occurrence data based on user-defined dictionaries. In addition, it includes a multidimensional concept-mapping sub-program called VBMap that measures the degree to which words co-occur in a text or series of texts. Miller, Andsager and Riechert (1998), for example, used the program to compare the press releases sent by 1996 GOP presidential candidates to the coverage the candidates received in the press. The program helped the researchers (a) generate a list of key words appearing in the text and (b) generate a map showing the relative positions of candidates, in both press releases and media coverage, to each other and on key issues in the election (e.g., family values, education). The program runs under DOS and is available for free from the software author’s website.

WordStat v5.0 (http://www.provalisresearch.com/wordstat/wordstat.html) This add-on to the Simstat statistical analysis program includes several exploratory tools, such as cluster analysis and multidimensional scaling, for the analysis of open-ended survey responses and other texts. It also codes based on user-supplied dictionaries and generates word frequency and alphabetical lists, KWIC, multi-unit data file output, and bivariate comparisons between subgroups. The differences between subgroups or numeric variables (e.g., age, date of publication) can be displayed visually in high resolution line and bar charts and through 2-D and 3-D correspondence analysis bi-plots. One particularly noteworthy feature of the program is a dictionary building tool that uses the WordNet lexical database and other dictionaries (in English and five other languages) to help users build a comprehensive categorization system.

The Yoshikoder (http://people.cbrss.harvard.edu/wlowe/CCA.html) Yoshikoder is a cross-platform multilingual content analysis program developed as part of the Identity Project at Harvard’s Center for International Affairs.

Major Text Analysis Resources

Text analysis, Semantics & Classification:

• www.analogx.com (English)
• www.cyberlex.pt (Spanish, Portuguese)
• www-306.ibm.com
• www.qsr.com.au (English, Japanese, Chinese)
• www.insightful.com (English)
• www.kdnuggets.com (English)
• www.ling.uqam.ca (English, French, Spanish)
• www.megaputer.com (English)
• www.nyu.edu (English)
• www.semantic-knowledge.com (English, French, Spanish, Portuguese)
• www.spss.com (English)
• sourceforge.net/projects/tamsys/ (English)
• www.textalyser.net (English)
• www.textanalysis.com (English)
• www.textquest.de (German, English, Spanish)
• www.mkms.xerox.com (English)

Spell checkers:

• www.allvirtualware.com (Spanish, French, German, English)
• www.afterscan.com (English, Russian)
• www.documens.com (English, French)
• www.alcodasoftware.com (English & 30 additional languages)
• www.lingsoft.fi (Swedish)
• www.spellex.com (English, Dutch, French, German, Italian, Russian,…)

Speech to Text:

• www-4.ibm.com (ViaVoice)
• www.microsoft.com/iit (Speech SDK)
• www.nuance.com (Dragon NaturallySpeaking)

To go to the Text analysis main page, click here.

source: http://www.textengines.com/analysis/links.htm

Statistical natural language processing and corpus-based computational linguistics: An annotated list of resources

Contents:

Tools: Machine Translation, POS Taggers, NP chunking, Sequence models, Parsers, Semantic Parsers/SRL, NER, Language models, Concordances, Summarization, Other
Corpora: Large collections, Particular languages, Treebanks, Discourse, WSD, Literature, Acquisition
SGML/XML
Dictionaries
Lexical/morphological resources
Courses, Syllabi, and other Educational Resources
Mailing lists
Other stuff on the Web: General, IR, IE/Wrappers, People, Societies

sources :

http://www-nlp.stanford.edu/links/statnlp.html

International Graduate Conference on Engineering and Science (IGCES) 2008

INTRODUCTION

Finding the frontier of knowledge in engineering and science faces significant challenges due to demand of rapid technology achievement and demand of globalization. The new technologies of engineering and science are nowadays moving at a tremendous pace by offering new feature and performance improvement in industries.

This conference is proposed to become an annual event of academics, scientist, and engineers all over the world to present and to exchange much ideas and their progress in researches. In line with educational process, this technical conference is designed to promote tremendous researches, enhance the skill in paper writing and oral presentation.
All the excellent papers and experiences gained in this conference will be much valuable to increase the quality of research and technology achievement.

Actually this IGCES is the continued of RPCES (Regional Postgraduate Conference on Engineering and Science) in 2006. The scope of call for paper submission is for Master and PhD student or it graduant.

DATE AND VENUE

The conference will be held during on 23-24 December 2008 at Universiti Teknologi Malaysia, Skudai Campus, Johor Bahru, Malaysia.

source : coutrtesy IGCES2008 http://beta.sps.utm.my/igces/

Riau Province – Indonesia

Riau, which includes a large part of East Sumatra, is homeland to Malays and the source of Indonesia’s Malay-based national language. The first book of Malay grammar, called Bustanul Katibin, was written and published here in 1857.

Pekanbaru became the provincial capital in 1959, taking over from the former capital of Tanjungpinang on the island of Bintan. About 160 kms upstream on the Siak River a number of buildings in the traditional style are still in this area, among them the Balai Dang Merdu the Balai Adat and Taman Budaya Riau, or Riau Cultural Park.

Tourist Office=]

Jl. Jend. Sudirman No.200, Pekan Baru Phone. (0761) 31452, 40356, Fax. (0761) 40356
http://www.budsenipar-riau.com

Riau Tourism Board

Gd. Badan Promosi & Investasi Prov. Riau, Lt. 2 Jl. Gajahmada 200, Pekanbaru – Riau
Tel/fax: +62-761-858441

Getting thereSimpang Tiga Airport is a busy visa free entry point. Pelangi flies to Kuala Lumpur and Silk Air flies to Singapore. Domestic airlines direct flights from Jakarta as well as from Medan and Batam. There are frequent departures from the bus station. Agencies all around town sell tickets for the boats to Batam.

Tourism Events

* Perahu Naga Festival, Tanjung Pinang. It is the Dragon Boat Race, both local and foreign contes, tank race a distance of 400 m.
* The event is held on Oct-08 at the Tanjung Pinang seaside facing Penyengat Island. To enhance the event there are culture performances, swimming competition for men and women and traditional diving contest.
* Pacu Jalur, Teluk Kuantan, Indragiri Hulu, Riau. Jalur or canoe races coincide with Indonesia’s Independedce Day celebration. Every decorative jalur used for the race on the Kuantan River is made of one single large bark of tree, approximately 30 m long and manned by 25-30 rowers. Before the festival was only held after a harvest and considered a sacred event. The event will be held on Aug 23-26 2008.
* Traditional Culture and Dance Parade on March, 2008 presents the Malay culture and traditions the event features a dance competition and dance performance from dance group and schools in city of Batam.

Places of Interest=]

Candi Muara Takus

Candi Muara Takus. Like many others structures of its kind in Sumatra, this Budha temple stupa near the village of Muara Takus in the Tigabelas Koto district, was built with red bricks and sand. The temple is believed to have been built at arround the 9th century A.D. when the power of the South Sumatra-bassed Sriwijaya Empire was at its peak. Excavations are still being made to determine the precise age and function of the stupa. It can be reached in 118 Km from Pekanbaru.

Muara Takus Temple

Kerumutan Nature Reserve

Kerumutan Nature Reserve. Located in mainland Riau in the Kuala Kampar district, this 120,000 hectares (30,000 acres) nature reserve can be reached in 18 hours by motor boat from Pekanbaru.

Kerumutan-nature-reserve

Bono

Bono is a curious natural phenomenon, which the Rokan River (in the Kampar regency) displays daily along its downstream reaches. Every day at the time high tide sets in, a swelling appears in the water at the river mouth. Accompanied by a rumbling sound, the swelling grows in mass until it is about as high as a small tree, spinning as it moves upwards along the river and growing smaller in the process until it finally disappears.

Dumai

Dumai. Formerly a fishing village on the east coast, it is now a major oil terminal. Storage tanks and modern installations rise against the sky, although the town itself is quite pleasant and interesting.

The Siak Sultanate’s Park

The Siak Sultanate’s Park. This Moorish style palace of the Sultan Siak, 120 kms upstream from Pekanbaru on the Siak River, was built in 1889 by Sultan Syarif Hasyim Abdul Jalil Syarifuddin. Now a museum, the palace contains the sultanate’s royal paraphernalia and others items of historical interest.

The Siak Palace

courtesy http://www.my-indonesia.info/

Title index

Bagi yang ingin mengkoleksi berbagai teks elektronik baik untuk riset atau sekedar baca2 saja, link dibawah mungkin bisa membantu. Terdapat berbagai jenis cerita dari berbagai penulis.
Selamat membaca

http://infomotions.com/alex/?cmd=titles

Catalogue of Electronic Texts -Alex

The Alex Catalogue of Electronic Texts is a collection of about 14,000 “classic” public domain documents from American and English literature as well as Western philosophy.

This is an alphabetical list of titles in the Catalogue.

A B C D E F G H I J K L M N O P Q R S T U V W X Y Z Other

1. The Pacha of Many Tales
2. Padre Ignacio; or, the song of temptation
3. Pagan Papers
4. The Pagan Tribes of Borneo
5. Pagan and Christian creeds: their origin and meaning
6. A Pagan of the Hills
7. The Pagans
8. Pages for Laughing Eyes
9. Pages from a Journal with Other Papers
10. Pages from an Old Volume of Life; a collection of essays, 1857-1881
11. Painted Windows
12. Painted Windows Studies in Religious Personality
13. A Pair of Blue Eyes
14. A Pair of Patient Lovers
15. The Palace Beautiful A Story for Girls
16. The Palace of Darkened Windows
17. Palamon and Arcite
18. The Palmy Days of Nance Oldfield
19. Pamela Giraud
20. Pamela, Volume II
21. Pamela, or Virtue Rewarded
22. Pan
23. Pandora
24. Panthea
25. Pantheism, Its Story and Significance Religions Ancient and Modern
26. Parables of a Province
27. The Parables of the Saviour The Good Child’s Library, Tenth Book
28. Paradise Garden The Satirical Narrative of a Great Experiment
29. Paradise Lost
30. The Paradise Mystery
31. Paradise Regained

etc,…..

Mathematic Related Tools and Information

Bagi yang ingin mencoba berbagai aplikasi dan fungsi dari matematika, situs berikut cukup menarik untuk dicoba.

Free Math Tools

Mathematic Calculation (Octave) – Powerful free on-line software tool for performing various mathematic calculation. It supports polynomials, matrix, integrals, derivates, differential equations and more.

Tutorial for Mathematic Calculations – Learn how to type operators, variables, matrices, arrays, functions in on-line tool above…

Simple financial mathematics calculators :

Compound Interest Calculator – Compound interest means that each time interest is paid, it is added to or compounded into the principal and thereafter also earns interest

Financial Lease Calculator – Calculation for your car leasing and other leasing types

Loan Calculator – Calculate your mortgage or other loan types or any other interest amortization

Present Value of Future Money – Find out how much your money will worth in future

Retirement Planning Calculator – Helps you choose your retirements savings