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A 6.3-magnitude earthquake struck early Sunday off Indonesia, according to the U.S. Geological Survey.
The quake rattled a remote swath of sea between the Pacific and Indian oceans, north of Australia and east of Timor-Leste, some 5.6 miles (9 kilometers) deep, according to the U.S. agency.
It was centered approximately 212 miles (340 kilometers) west-northwest of Saumlaki in Indonesia's Tanimbar Islands, 217 miles east-northeast of Dili, Timor-Leste, and 226 miles of Ambon, Indonesia.
Neither the Pacific Tsunami Warning Center nor the Japan Meteorological Agency issued tsunami warnings or advisories immediately after the tremor.
 
STORY HIGHLIGHTS
  • The quake rattles a remote swath of sea between the Pacific and Indian oceans
  • It is 9 kilometers deep and was centered 212 miles from Saumlaki, Indonesia
  • No tsunami warnings or advisories are immediately issued

By CNN Staff
December 1, 2013 -- Updated 0204 GMT (1004 HKT)

 

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A music-based training program that challenges both the body and the mind may improve brain function and mood among seniors, suggests a new study from Switzerland.

"The take-home message is that 6-months of music-based multitask training (i.e., Jaques-Dalcroze eurhythmics) - a specific training regimen which was previously shown to be effective in improving gait and reducing falls - has beneficial effects on cognition and mood in older adults," Dr. Mélany Hars, of Geneva University Hospitals, told Reuters Health in an email.

Jacques-Dalcroze eurhythmics was developed in the early part of the 20th century by the Swiss composer Emile Jaques-Dalcroze as a way to better understand music through movement. It is practiced worldwide, particularly in the fields of music, theater, dance and therapy, according to Hars.

A typical Jacques-Dalcroze session involves participants adapting their movements to the rhythmic changes of improvised piano music. In Hars' study, the participants were challenged to perform specific multitasking skills, such as walking to the rhythm of a piano while handling a percussion instrument and responding to changes in the piano's rhythm.

The study participants were also asked to perform quick reaction exercises, such as starting or stopping to walk or changing their walking speed on command, as well as matching their steps to the long or short music notes that were played.

The study included 134 men and women aged 75 years, on average, who were all at increased risk for falls but who did not live in a nursing home or other facility. These seniors were randomly divided into a study group that attended hour-long music-based multitasking sessions once a week for 25 weeks or a comparison group that just kept up their normal lifestyles and did not attend training sessions.

At the beginning of the study, both groups underwent a battery of tests for mental function and mood.

After six months, the 66 adults who participated in the music training sessions showed improved cognitive function, particularly on a test of their degree of sensitivity to interference, and decreased anxiety, compared to the group that had not done the training.

"This may have implications for everyday life function," since many situations require individuals to pay selective attention to one thing while blocking out something else, such as distracting surroundings, Hars and her coauthors write in the journal Age and Ageing.

How the training might be responsible for the improvements is unknown, Hars acknowledges.

However, she noted, "some studies suggest that music can mitigate effects of the aging brain… (and) some studies have revealed that specific physical exercise regimens may enhance (not only) cognitive performance but also brain function or brain structure of older adults."

Jacques-Dalcroze eurhythmics puts it all together in a program that combines gait, balance, movement coordination and flexibility training while also engaging attention and memory skills, Hars said.

This "is likely to engage multiple brain regions through a combination of music, rhythm, and exercise," Hars said.

Whether the training is also linked with fewer falls or improved walking ability in these seniors remains to be studied, the researchers point out in their report.
mson/Reuters. All rights reserved.

CS 276/286 LING: Information Retrieval dan Web Cari Spring 2013
Chris Manning, Pandu Nayak, dan Prabhakar Raghavan
Kursus Info Silabus Coursera Piazza Buku

CS 276/286 LING: Retrieval Informasi dan Web Search
Kuliah: 3 unit, Tu / Th 4:15-05:30 di Auditorium NVIDIA (tersedia secara online melalui SCPD )
Staf e-mail: cs276-spr1213-staff@lists.stanford.edu

Kursus Deskripsi

Teknik dasar dan lanjutan untuk sistem informasi berbasis teks: pengindeksan teks efisien, Boolean dan vektor model pengambilan space, masalah evaluasi dan antarmuka, pencarian Web termasuk merangkak, algoritma berbasis link-, dan Web metadata, pengelompokan teks / Web, klasifikasi; pertambangan teks .
Kebijakan Informasi (grading, dll)
Prasyarat: CS 107, CS 109, CS 161. Idealnya seluruh CS Mayor Inti.

Online Resources

Coursera: CS 276 akan memanfaatkan video online dan kuis serta ceramah hidup kelas, presentasi, dan laboratorium. Kunjungi Coursera untuk menemukan potongan video dan latihan online. Kami akan posting tugas pemrograman yang diperlukan dan masalah set melalui Coursera, jadi mendaftar segera (dengan Stanford ID Anda)!
Piazza: Kami sangat menyarankan agar Anda posting pertanyaan tentang tugas, kuliah atau materi kuliah umum di Piazza . Ini memfasilitasi diskusi antara siswa, dan memungkinkan orang lain untuk mendapatkan keuntungan dari diskusi juga. Bahkan jika Anda pikir pertanyaan Anda adalah khusus untuk pelaksanaan Anda, Anda dapat menggunakan fitur 'pertanyaan pribadi' untuk mengatasi pertanyaan kepada staf khusus. Kami akan menggunakan Piazza untuk mengirim saja pengumuman, jadi pastikan untuk mendaftar di Piazza segera juga. Berikut adalah cepat pengenalan video .
Staf Email: Jika Anda benar-benar memiliki pertanyaan tentang situasi Anda secara khusus, bahwa Anda tidak berpikir tidak sesuai untuk forum kelas (bahkan bukan pertanyaan pribadi), silahkan email staf mailing list di cs276-spr1213-staf @ daftar. stanford.edu .
Pengumuman:
Jika Anda tidak terdaftar dalam kursus tapi ingin menerima saja pengumuman, Anda dapat berlangganan ke mailing list tamu cs276-spr1213-tamu .

CS 276 Informasi Staf

Profesor:
Chris Manning , Jam Kantor: Wednesday 3-4 PM, Gates 158
Pandu Nayak , Jam kantor: setelah kelas dengan pengaturan sebelumnya
Prabhakar Raghavan , Jam kantor: setelah kelas dengan pengaturan sebelumnya
TA: Sonal Gupta (Kepala TA), Shui Hu, Anshul Mittal, Rukmani RaviSundaram, Thang Luong

Jam TA Office

Untuk jadwal rinci, memeriksa kalender Google menggunakan ID: f0qejqeg52qo292jk3i44lqd04@group.calendar.google.com
Jam Daytime Office
  • Senin: Gates B24A 10 11:00
  • Rabu: Gates B26B 11:00-12:00
  • Jumat: Gates B26B 10 11:00
Coding Sesi
  • Selasa: Bldg 160 Room 332 6-9
  • Rabu: Bldg 160 Room 332 6-09:00
Untuk siswa SCPD, kami akan tersedia melalui Google hangout, link yang akan diposting di Piazza.

Silabus

Rincian jadwal, video, slide dan daftar bacaan akan diperbarui sebagai kuartal berlangsung.
Tanggal Dalam Kelas Tugas Siapa Bahan
Tue 2 Apr Pengantar saja: Diskusi isu dalam pencarian ditambah Web 1: pencarian Web, iklan, SEO
PN Coursera:
Boolean Retrieval (IIR Ch. 1)
Catatan:
[ powerpoint ]
[ PDF / 6 ]
[ PDF / 1 ]
Bacaan:
IIR Ch. 1
MG 3.2
MIR 8.2
Drama Shakespeare
Thu 4 Apr Pembicara tamu: Jeff Dean pada evolusi pencarian Google dan sistem pencarian PA1 out Jeff Coursera:
Daftar Kosakata Syarat dan Postingan (IIR Ch. 2)
Catatan:
[ powerpoint ]
[ PDF / 6 ]
[ PDF / 1 ]
Bacaan:
IIR Ch. 2
MG 3.6, 4.3
MIR 7.2
Stemmer Porter (MIR) , Porter berasal algoritma (Official)
Daftar melewatkan masak (Pugh 1990)
Frase cepat query dengan indeks gabungan (Williams, Zobel, Bahle 2004)
Frase efisien query dengan indeks tambahan (Bahle, Williams, Zobel 2002) MapReduce: pengolahan data disederhanakan pada kelompok besar (Dean dan Ghemawat 2004)
Tue 9 Apr Kelas laboratorium: Menulis algoritma merge untuk kedekatan query menggunakan indeks posisional
PrimaryPad
Bersama gdoc: http://bit.ly/HgCAdP
Persimpangan kerangka
Kerangka Positional
Jawaban Positional
[Membutuhkan sunet ID]
PS1 Out CM Coursera:
Index Konstruksi (IIR Ch. 4)
Catatan
[ powerpoint ]
[ PDF / 6 ]
[ PDF / 1 ]
Bacaan
IIR Ch. 4
MG Ch. 5
Konstruksi yang efisien indeks single-pass untuk database teks (Heinz dan Zobel 2003)
Thu 11 Apr Lab kelas: Algoritma untuk daftar posting kompresi
PrimaryPad
compress.py
Hasil gdoc spreadsheet
Slide kompresi Jeff Dean
Simple-9 (Anh / Moffat)
Wikipedia: Golumb / Beras , Huffman , kode gamma Elias , kode unary

CM Coursera:
Indeks Kompresi (IIR Ch. 5)
Catatan:
[ powerpoint ]
[ PDF / 6 ]
[ PDF / 1 ]
Bacaan:
IIR Ch. 5
MG 3.3, 3.4
Kompresi indeks terbalik untuk evaluasi permintaan cepat (Scholer et al 2002.)
Kompresi indeks terbalik menggunakan kode biner kata-blok (Anh dan Moffat 2005)
Tue 16 Apr Koreksi ejaan
[ powerpoint ]
[ PDF / 6 ]
[ PDF / 1 ]
Karena PS1 PR Coursera:
Kamus dan Toleran Retrieval (IIR Ch. 3)
Catatan:
[ powerpoint ]
[ PDF / 6 ]
[ PDF / 1 ]
Bacaan:
Bagaimana menulis korektor ejaan (Peter Norvig)
IIR Ch. 3
MG 4.2
Teknik untuk secara otomatis mengoreksi kata-kata dalam teks (Kukich 1992)
Menemukan pertandingan perkiraan dalam leksikon besar (Zobel dan Dart 1995)
Generasi dan PERINGKAT Spelling Koreksi Kesalahan (Tillenius) Efisien
Thu 18 Apr Lab Kelas: Mapreduce dengan Python
PrimaryPad
mapreduce.py
count_words.py
lmtrain.py
idf.py
index.py
anchors.py
index_with_anchors.py
PA1 karena
PA2 out
PN Coursera:
Vector Space Model (IIR Ch. 6)
Catatan:
[ powerpoint ]
[ PDF / 6 ]
[ PDF / 1 ]
[ Jeff Dean Slides ]
Bacaan:
IIR 6.2 - 6.4.3
Tue 23 Apr Probabilistic IR: Binary Independence Model
[ powerpoint ]
[ PDF / 6 ]
[ PDF / 1 ]
PS2 Out PN Bacaan:
IIR 11
Thu 25 Apr BM25, BM25F, dan sinyal peringkat [ powerpoint ]
[ PDF / 6 ]
[ PDF / 1 ]

PN Bacaan:
IIR 11
Tue 30 Apr Evaluasi. Presisi / ingat, NDCG, dengan menggunakan rasio klik per tayang
[ powerpoint ]
[ PDF / 6 ]
[ PDF / 1 ]
Karena PS2 PR Bacaan:
IIR Ch. 8
MG 4.5
MIR Ch. 3
Thu 2 Mei Masalah sistem dalam temu efisien dan scoring
[ powerpoint ]
[ PDF / 6 ]
[ PDF / 1 ]
PA2 karena
PA3 out
PR Coursera:
Skor Computing (IIR Ch. 7)
Catatan:
[ powerpoint ]
[ PDF / 6 ]
[ PDF / 1 ]
Bacaan:
IIR Ch. 7 , IIR 6.1
Tue 7 Mei Lucene Tutorial
[ powerpoint ]
[ PDF / 6 ]
[ PDF / 1 ]
PS3 Out PN
Thu 9 Mei KLASIFIKASI 1 + 2: Naif Byes, kNN, batas keputusan
[ powerpoint ]
[ PDF / 6 ]
[ PDF / 1 ]

PR Bacaan:
IIR Ch. 11
IIR Ch. 13
Mesin pembelajaran dalam kategorisasi teks otomatis (Sebastiani 2002)
Sebuah pemeriksaan ulang metode kategorisasi teks (Yang et al. 1999)
Perbandingan model event untuk naif Bayes klasifikasi teks (McCallum et al. 1998)
Tom Mitchell. Machine Learning. McGraw-Hill, 1997.
Buka Calais
Weka
Reuters-21578
Mengatasi asumsi miskin Naive Bayes classifier (Rennie et al. 2003)
IIR Ch. 14
Mesin pembelajaran dalam kategorisasi teks otomatis (Sebastiani 2002)
Tom Mitchell. Machine Learning. McGraw-Hill, 1997.
Sebuah pemeriksaan ulang metode kategorisasi teks (Yang et al. 1999)
Mengevaluasi dan mengoptimalkan sistem klasifikasi teks otonom (Lewis 1995)
Trevor Hastie, Robert Tibshirani, Jerome Friedman Elemen statistik Learning:. Data Mining, Inferensi, dan Prediksi. Springer-Verlag, New York, 2001.
Tue 14 Mei KLASIFIKASI 3. Mesin dukungan vektor
[ powerpoint ]
[ PDF / 6 ]
[ PDF / 1 ]
Karena PS3 CM Bacaan:
IIR Ch. 15
Sebuah tutorial pada mesin dukungan vektor untuk pengenalan pola (Burges 1998)
Menggunakan SVM untuk teks kategorisasi (Dumais1998)
Algoritma pembelajaran induktif dan representasi untuk teks kategorisasi (Dumaiset a. 1998)
A Re-pemeriksaan metode kategorisasi teks (Yang et al. 1999)
Teks kategorisasi berdasarkan metode klasifikasi linear regularized (Zhang et al. 2001)
Trevor Hastie, Robert Tibshirani, Jerome Friedman Elemen statistik Learning:. Data Mining, Inferensi, dan Prediksi. Springer-Verlag, New York, 2001.
Reuters-21578
Thorsten Joachims. Belajar untuk Klasifikasikan Teks menggunakan Support Vector Machines. Kluwer, 2002.
Sebuah analisis fungsi kerugian untuk metode klasifikasi dalam teks kategorisasi (Li et al. 2003)
Thu 16 Mei Web 2: Belajar untuk peringkat.
[ powerpoint ]
[ PDF / 6 ]
[ PDF / 1 ]
PA3 karena
PA4 out
CM Bacaan:
IIR 6.1.2-3 , IIR 15.4
Model diskriminatif untuk pencarian informasi (Nallapati 2004)
Beradaptasi peringkat SVM untuk mendokumentasikan pengambilan (Cao et al. 2006)
Sebuah metode vektor dukungan untuk mengoptimalkan presisi rata-rata (Yue et al. 2007)
Dataset LETOR patokan
Tue 21 Mei Diundang bicara: Sriram Sankar dari Facebook pada Grafik Pencarian
Sriram Sankar
Thu 23 Mei CLUSTERING 1: k-means, HAC
[ powerpoint ]
[ PDF / 6 ]
[ PDF / 1 ]

PN Bacaan:
IIR Ch. 16 , IIR 17,1-3
Tue 28 May CLUSTERING 2. LSI
[ powerpoint ]
[ PDF / 6 ]
[ PDF / 1 ]
PS4 Out CM Bacaan:
IIR Ch. 18
Thu 30 Mei Web 3: Analisis Link.
[ powerpoint ]
[ PDF / 6 ]
[ PDF / 1 ]
PA4 karena PR Bacaan:
IIR Ch. 21
Peringkat perbatasan web (Eiron et al. 2004)
Kerangka WebGraph I: teknik kompresi (. Boldi et al 2004)
Metode ekstrapolasi untuk mempercepat perhitungan PageRank (Kamvar et al. 2003)
Mencari web kerja (Fagin et al. 2003
Tue 4 Jun Web 4: Crawling, dekat-dups PS4 karena PR Catatan:
[ powerpoint ]
[ PDF / 6 ]
[ PDF / 1 ]
Bacaan:
IIR Ch. 20
Mercator: A scalable, web crawler extensible (. Heydon et al, 1999)
Sebuah standar untuk pengecualian robot
Thu 6 Jun Tidak ada kelas.


Fri 7 Jun Ujian akhir (12:15-3:15)
Praktek Akhir
Praktek Solusi Akhir



Diperlukan Textbook:

IIR = Pengantar Information Retrieval, oleh C. Manning, P. Raghavan, dan H. Schütze. Cambridge University Press, 2008.
Buku ini tersedia dari toko buku Stanford (atau penyetor buku favorit Anda). Anda juga dapat men-download dan bab cetak di situs buku . (Kami akan menghargai setiap laporan kesalahan ketik atau masalah-tingkat yang lebih tinggi untuk pencetakan ketiga. Terima kasih.)

Lainnya Baik IR Books:

MG = Mengelola Gigabytes, oleh I. Witten, A. Moffat, dan T. Bell.
Irah = Information Retrieval: Algoritma dan Heuristic oleh D. Grossman dan O. Frieder.
MIR = Informasi modern Retrieval, oleh R. Baeza-Yates dan Ribeiro-Neto B..
FOA = Menemukan Out Tentang, oleh R. Belew.
MTW = Pertambangan Web, oleh S. Chakrabarti.
FSNLP = Yayasan Statistik Natural Language Processing, oleh C. Manning dan H. Schütze.
Buku-buku ini semua memiliki informasi yang berguna tentang topik yang kita bahas dan direkomendasikan sebagai referensi. MG sangat baik sebagai referensi rinci untuk IR teknis pada semester pertama tentu saja. MTW mencakup banyak topik dari bagian akhir kursus.

Lebih banyak sumber daya rinci dapat ditemukan di sini .

Dosen:

CM = Chris Manning
PN = Pandu Nayak
PR = Prabhakar Raghavan
Program terkait:
Pengantar Komputasi Advertising ( http://www.stanford.edu/class/msande239/ )

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"Did I not tell you that we of the ruling class owned all the land, all the forest, everything? Any food-getter who would not get food for us, him we punished or compelled to starve to death. And very few did that. They preferred to get food for us, and make clothes for us, and prepare and administer to us a thousand—a mussel-shell, Hoo-Hoo—a thousand satisfactions and delights. And I was Professor Smith in those days—Professor James Howard Smith. And my lecture courses were very popular—that is, very many of the young men and women liked to hear me talk about the books other men had written.

"And I was very happy, and I had beautiful things to eat. And my hands were soft, because I did no work with them, and my body was clean all over and dressed in the softest garments—
"He surveyed his mangy goat-skin with disgust.

"We did not wear such things in those days. Even the slaves had better garments. And we were most clean. We washed our faces and hands often every day. You boys never wash unless you fall into the water or go swimming."

"Neither do you Granzer," Hoo-Hoo retorted.

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"I know, I know, I am a filthy old man, but times have changed. Nobody washes these days, there are no conveniences. It is sixty years since I have seen a piece of soap.

"You do not know what soap is, and I shall not tell you, for I am telling the story of the Scarlet Death. You know what sickness is. We called it a disease. Very many of the diseases came from what we called germs. Remember that word—germs. A germ is a very small thing. It is like a woodtick, such as you find on the dogs in the spring of the year when they run in the forest. Only the germ is very small. It is so small that you cannot see it—"

Hoo-Hoo began to laugh.

"You're a queer un, Granser, talking about things you can't see. If you can't see 'em, how do you know they are? That's what I want to know. How do you know anything you can't see?"
"A good question, a very good question, Hoo-Hoo. But we did see—some of them. We had what we called microscopes and ultramicroscopes, and we put them to our eyes and looked through them, so that we saw things larger than they really were, and many things we could not see without the microscopes at all. Our best ultramicroscopes could make a germ look forty thousand times larger. A mussel-shell is a thousand fingers like Edwin's. Take forty mussel-shells, and by as many times larger was the germ when we looked at it through a microscope. And after that, we had other ways, by using what we called moving pictures, of making the forty-thousand-times germ many, many thousand times larger still. And thus we saw all these things which our eyes of themselves could not see. Take a grain of sand. Break it into ten pieces. Take one piece and break it into ten. Break one of those pieces into ten, and one of those into ten, and one of those into ten, and one of those into ten, and do it all day, and maybe, by sunset, you will have a piece as small as one of the germs." The boys were openly incredulous. Hare-Lip sniffed and sneered and Hoo-Hoo snickered, until Edwin nudged them to be silent.

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The incubators are built in remote fastnesses, where there is little or no likelihood of their being discovered by other tribes. The result of such a catastrophe would mean no children in the community for another five years. I was later to witness the results of the discovery of an alien incubator.
The community of which the green Martians with whom my lot was cast formed a part was composed of some thirty thousand souls. They roamed an enormous tract of arid and semi-arid land between forty and eighty degrees south latitude, and bounded on the east and west by two large fertile tracts. Their headquarters lay in the southwest corner of this district, near the crossing of two of the so-called Martian canals.

As the incubator had been placed far north of their own territory in a supposedly uninhabited and unfrequented area, we had before us a tremendous journey, concerning which I, of course, knew nothing.

After our return to the dead city I passed several days in comparative idleness. On the day following our return all the warriors had ridden forth early in the morning and had not returned until just before darkness fell. As I later learned, they had been to the subterranean vaults in which the eggs were kept and had transported them to the incubator, which they had then walled up for another five years, and which, in all probability, would not be visited again during that period.

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