Mitul Tiwari's blog

Supervised Random Walk for link prediction

2011-05-15T16:11:00.003-05:00

Last week in our reading group at LinkedIn we discussed "Supervised Random Walks: Predicting and Recommending Links in Social Networks" by L. Backstrom and J. Leskovec, which appeared in ACM Internation Conference on Web Search and Data Mining (WSDM), 2011.

This is quite interesting paper that talks about link prediction problem. Link prediction is a fundamental problem in a graph or social networks to predicts edges/links that don't exist currently but may appear in future. Applications of link prediction includes (1) "People You May Know" feature in social networks such as LinkedIn or Facebook, (2) predict links in protein-protein interaction, (3) suggest links to bloggers to add, (4) predict collaboration, etc.

In the past there has been two main approaches to link prediction in a graph: (1) classification potential edges as positive or negative using various features from the graph; and (2) random walk on the graph to rank nodes by assigning probability to each node.

In the first approach, various features such as node (e.g., age, gender), edge (e.g., interaction, activity), graph (e.g., the number of common friends) are used to predict links. Past edges can be used as labeled training data to classify potential edges as positive or negative edges in the future.

In the second approach, random walks are used to assign probabilities to nodes, and rank nodes based on these probabilities. Higher the rank, more likely it is to be an edge between the starting node and that node. Random walks have been used to find out important nodes in a graph (like Pagerank) and also used for finding similar nodes in a graph. Random walk with restarts is one example of this approach.

This paper talks about how to combine these two approaches into one by building a model to bias a random walk in a graph, and use the random walk for link prediction. Node and edge (e.g., the number of common friends) features are used to learn transition probabilities between edges. And then random walk with restart is run to find out a probability score for each node. Nodes are ordered by these probability score to find out the top nodes that are likely to be connected with the starting node in the future.

This is quite interesting approach that does not need complicated feature engineering to find out graph features, but this approach is very compute intensive since random walk takes multiple iterations of graph traversal, and if the graph is huge (say 100s of millions of nodes) then it will take a long time to run. In my experience, frequently running link prediction pipeline is more important then marginal improvement in link prediction accuracy since online social graph changes continuously.

Nevertheless, this paper brings very interesting ideas to combine the classification approach and the random walk approach for link prediction.

References

Supervised Random Walks: Predicting and Recommending Links in Social Networks, L. Backstrom and J. Leskovec. In Proceedings of the 4th ACM international conference on Web search and data mining.
Link Prediction Problem for Social Networks, D. Liben-Nowell and J. Kleinberg. In Proceedings of 12th International Conference on Information and Knowledge Management (CIKM), 2003.
Predicting Positive and Negative Links in Online Social Networks, J. Leskovec, D. Huttenlocher and J. Kleinberg. In Proceedings of 19th International World Wide Web Conference (WWW), 2010.

Summary of Haystack system paper from Facebook

2011-04-28T23:15:00.004-05:00

This week in our reading group at LinkedIn we read and discussed this paper: Finding a needle in Haystack: Facebook's photo storage.

As the name suggests the Haystack system is designed and built by Facebook guys to store and serve photos.

The basic goals of Haystack system are as follows: first, high throughput and low latency, store all metadata in main memory, and save on multiple disk I/Os. They are able to achieve 4x speedup than the earlier system by doing this. Second, fault-tolerance. Replicate photos across multiple data centers. Third, cost-effectiveness. They claim to be 28% cheaper than the earlier system.

In the earlier NAS (Network Attached Storage) photo storage system, the main bottleneck was 3 disk accesses for fetching each photo: one for fetching the location of corresponding inode, second for reading inode, and third for fetching the file data.

The main idea of the Haystack system is the design of Haystack store that lead to fetching of a photo in a single disk access. In the Haystack store, they keep multiple photos in a single large file. They need only the offset of the photo in the file and size of the photo to access a photo. This way they are able to reduce the amount of metadata needed to access a photo, and keep all metadata for photos in memory. Hence, no disk access is needed to fetch the metadata for a photo and the photo can be fetched from the disk in a single disk access.

Overall, impressed by the scale of Haystack photo storage system that stores more than 20 Petabytes in form of 260 billions of photos and serves millions of photos per second at the peak.

Reference:

D. Beaver, S. Kumar, H. C. Li, J. Sobel, and P. Vajgel. Finding a needle in Haystack: Facebook’s photo storage. In OSDI ’10

Effectiveness of data

2010-04-12T18:09:00.003-05:00

I attended a talk by Dr. Peter Norwig last week at "The Analytics Revolution Conference" on "The Unreasonable Effectiveness of Data". He talked about how having large amount of data changes the results/outcome, how simpler algorithm works much better with more data than a complex algorithm with less data. He showed three examples to support his case: (1) Spelling correction; (2) Google image search; and (3) Google translation.

(1) Spelling correction. Dr. Norwig talked about underlying principles behind Google's spelling correction. He talked about how frequency of terms in web data is used to figure out possible suggestions and how to score each of the suggestion. For a given query w, Google computes the most likely spelling correction for the query. This is done by computing

argmax_c P(c|w) = argmax_c P(w|c) P(c) (after ignoring P(w) which is same for the given query w)

where,

P(c) is computed using the number of times c occurs in the web corpus. P(w|c) is computed using edit distance between w and c.

So a simple frequency based spelling correction algorithm performs well and in practice works much better than dictionary based algorithm. Also, it is language independent so it works for any language by just changing the input web data. For more details, see Peter Norwig's blog post on spelling correction:

2. Image search. Dr. Norwig talked about how Google constructs similarity graph of crawled images, and how for a given query, dense clusters of images in the graph are likely to be the best quality images. Here also large numbers of images help in improving result.

3. Google translation. Google translation has been sited by many Googlers as a major success of using large amount of data. Dr. Norwig reiterated this point, and talked about how simple co-occurrence of phrases from two different languages is used by Google translation to translate between the two languages.

Organizing the Web around Concepts

2009-09-30T17:01:00.004-05:00

During the initial days of the web, directories like Yahoo manually organized the web to find the relevant information. As web grew in size and search engine technology evolved, search engines like Google became the main source to query the web. Today, we see the next wave is making the web navigation easier by reorganizing the internet by topic or concept, and increasingly meaningful web (which may lead to Semantic Web) is being built around concepts such as Freebase, Google Squared, DBLife, and Kosmix topic pages. At Kosmix, we often ask the technical philosophy driving this change. Here is a brief overview for the geeks among us.
To start with, what do we mean by concepts? A concept is loosely defined as a set of keywords of interest, for example, the name of a restaurant, cuisine, event, name of a movie, etc. There are various websites tailored to a particular kind of concept such as Yelp for restaurants (e.g., Amarin Thai), IMDB for movies (e.g., The Shawshank Redemption), LinkedIn for professional people, Last.fm for music (e.g., U2), etc.
Why should one care about organizing the web around concepts? There are three main kinds of web pages: search pages, topic/concept pages, and articles. Organizing the web around concepts can benefit each one of them.
Search pages. A search results page for a given query consists of various relevant links with snippets, for example, Google search results pages on "Erykah Badu". Web data around concepts can improve search results in two ways. First, a search page can show a bunch of concepts related to the query, and their relationships to the query. This will help in further refining the query, and enable exploration of concepts related to the query. Second, a search page can promote the concept page result for a concept closely matching the query.
Concept/Topic pages. A topic page or concept page organizes information around a concept, for example consider this music artist page on "Erykah Badu". Such pages can utilize attributes of concepts, and show content related to the concept and its attributes, such as, albums, music videos, songs listing, album reviews, concerts, etc.
Articles. Articles can put semantic links to the concepts present in the article, and promote exploration of concepts present in the article, for example, this page on oil prices.
Given so many benefits of arranging the web around concepts, how can we achieve that? Some of the ways to arrange the web around concepts are as follows.
1. Editorial: An editor can pick a set of interested concepts, create attributes of the concepts, and organize the data around the concepts. Many sites like IMDB (for movies) have taken this approach. This approach gives high quality content but it's not scalable in terms of the number of concepts.
2. Community: Many sites such as Wikipedia and Yelp have taken this approach in which a community of users picks concepts, creates the attributes of the concepts, and organizes the data around the concepts. This process scales as the user community grows, but it is hard to build such community, this approach is susceptible to spam, and scale is limited. For example, Wikipedia has grown to millions of concepts with such a large user base, but it size is still far from the scale of the web.
3. Algorithmic approach: One way to organize the web around concepts is to mine the web for concepts and their attributes, and link data with concepts. This approach is the most promising in terms of scaling to the size of the web. Various steps in this approach are (a) Concept Extraction, (b) Relationship mining, and (c) Linking data with concepts.
(a) Concept Extraction. There are two main methods for concept extraction from web pages, site-specific and category-specific.
In the site specific method, the structure or semantics of a site is used to extract concepts. Many web sites generate HTML pages from the databases through a program, and such pages have similar structure. One can write site specific rules or wrappers to extract interesting data from such web pages, but writing such wrappers is labor intensive task. Kushmerick et. al. have proposed wrapper induction technique to automatically learn wrapper procedures based upon samples of such web pages. A recent work by Dalvi et. al. extends the wrapper induction technique to dynamic web pages. Another site specific method is to use natural language processing to understand semantic of web pages and to mine concepts from web pages.
In the category specific method, web pages are classified into categories, such as, restaurants, shopping, movies, etc., and category specific extraction rules are applied. For example, extract menu, reviews, cuisine, location for restaurants; extract price, reviews, ratings for shopping category; and extract actors, director, ratings for movies. This method is more scalable in terms of the number of web pages compared to the site specific method, but slightly more error prone since classification and extraction errors accumulate.
(b) Relationship mining. After extracting interesting concepts, one needs to match them with concepts in the database to create attributes, to grow concepts, and to find relationships between concepts. Some web databases like Freebase provide substantial amount of relationships between Wikipedia concepts.
(c) Linking data with concepts. As mentioned earlier, organizing web around concepts can benefit experience with search pages, topic pages, and article pages by linking them with concepts.
The algorithmic approach to organizing the web around concepts is somewhat error prone, though it improves as algorithms for a particular step improves. However, it is most promising in terms of scaling to enormous web that exists.
In short, organizing the web around concepts is a promising area and a stepping stone to bring meaning behind the web data.
References
[1] N. Kushmerick, D. S. Weld, R. B. Doorenbos: Wrapper Induction for Information Extraction. IJCAI (1) 1997.
[2] N. Dalvi, P. Bohannon, F. Sha: Robust web extraction: an approach based on a probabilistic tree-edit model. SIGMOD Conference 2009.

Deep Web: The Hidden Treasure

2009-08-10T16:47:00.014-05:00

(Iceberg image ©Ralph A. Clevenger)

Experts estimate that search engines can access less than 1% of the data available on the Web, only the tip of the iceberg. Where is the rest of Internet’s data? It’s lurking in the Deep Web.

What is the Deep Web?

The Deep Web is defined as dynamically generated content hidden behind HTML forms that is inaccessible for search engines' crawlers. Deep Web is also referred as the hidden or invisible Web.

The Deep Web consists of three key elements: (1) pages and databases accessible only through HTML forms; (2) disconnected pages not accessible to crawlers; and (3) password protected and subscription only sites. Some people also include real time Web data as a part of the Deep Web, since it's changing so fast that traditional search engines are not able to surface it in their results.

How Vast is the Deep Web?

According to one study by Michael K. Bergman in 2000, the Deep Web accounted for 7,500 terabytes of data. At that time, search engines could index only 10s of terabytes of data. By 2004, a subsequent study by Kevin Chang and his colleagues estimated that the Deep Web had grown to more than 30,000 terabytes of data. At this rate, one can only imagine how vast it must be today, particularly given the ubiquity of the Internet over the past five years. Such
an enormous amount of data has huge wealth of information—the key is figuring out how to access it.

Is it Possible to Access the Deep Web?

Absolutely-though it’s not easy. There are two main approaches to accessing Deep Web data: run-time integration, and off-line indexing.

In the run-time integration approach, one has to build a system that performs the following tasks: first, figure out the appropriate forms that are likely to have results for the given query terms; second, map the query terms suitably to search those forms and integrate the results from various forms; and third, extract relevant parts of results to display. This approach enables richer experience for users, and sites like Cazoodle.com seems to rely on this method.

But there are some drawbacks to run-time integration. It’s extremely difficult to figure out appropriate forms for the given query terms. In addition, mapping query terms to search those forms and extracting information from the results is highly labor-intensive tasks and not very scalable.

In the off-line indexing approach to access Deep Web data, one has to construct a set of queries to search through forms, process the queries through forms while off-line, and index the result. Once the query set is constructed, this approach can reuse the search engine infrastructure for crawling, indexing results, and index serving.

Google has taken this approach to surface Deep Web content. However, algorithmically constructing input values for forms is a non-trivial task. Furthermore, this approach cannot be applied to HTML forms that use HTTP POST method, since the resulting URLs are the same, and form inputs are part of HTTP request rather then the URL.

The Kosmix Approach to the Deep Web

At Kosmix, we surface Deep Web content by using a combination of run-time integration and off-line indexing approaches. At the core of Kosmix technologies are (1) a sophisticated categorization engine that enables mapping of query to appropriate category; (2) a highly scalable fetching and run time integration system to fetch data from various sources, integrate, and provide rich experience; and (3) an off-line crawling and indexing systems that enables
scalability.

For example, for a query like "Ravioli", we show nutritional values from Fatsecret.com. Our categorization technology enables us to identify Ravioli as a food query, and enables us to surface Deep Web content from Fatsecret.com.

The Next Hurdle

While invaluable treasures are hiding behind the Deep Web, there are significant challenges to solving the problem of reaching this information. The next step for search engines will be to find an easier way to tap into the Deep Web, and to keep up with the Real Time Web.

My prediction? The Deep Web will force a drastic change in how traditional search engine systems are designed and built.

References:

Michael K. Bergman. White Paper: The Deep Web: Surfacing Hidden Value. http://brightplanet.com/index.php/white-papers/119.html, 2000.
Kevin Chen-chuan Chang, Bin He, Chengkai Li, Mitesh Patel, and Zhen Zhang. Structured Databases on the Web: Observations and Implications. In SIGMOD 2004.
Cazoodle. http://www.cazoodle.com/docs/Press_Kit.pdf, 2009.
Jayant Madhavan, David Ko, Lucja Kot, Vignesh Ganapathy, Alex Rasmussen, and Alon Halevy. Google's Deep Web crawl. In VLDB 2008.

2008-12-09T02:58:00.004-06:00

Kosmix launched a new beta-ish version today. Check out this post explaining what's new in the beta version: "Kosmix goes betaish".

We also announced $20 million funding from Time-warner and others: "Kosmix adds rocketfuel".

How is Kosmix different from a search engine? Search engines treat web as a collection of documents. In contrast, we treat web as a collection of applications, and bring together the best of the web applications relevant to the given query on one page, and present them in a two dimensional layout. Our categorization technology helps in figuring out the category of the query, and picking the best applications. Check out a few examples: Simpsons, San Francisco, Diabetes, Acura TSX.

Check out Anand's blog for more details.

iPhone 3G disassembly

2008-07-24T02:45:00.001-05:00

iPhone 3G disassembly: http://live.ifixit.com/Guide/First-Look/iPhone3G

PhD comic on F-1 students

2008-07-11T16:55:00.001-05:00

Life of F-1 students, PhD comics sums it all: F-1 students visa process :)

Hilarious video on Onion

2008-06-05T03:02:00.001-05:00

Check out this hilarious video: New Wearable Feedbags Let Americans Eat More, Move Less :) ...

My comments on "Why the World Needs a New Database System"

2008-05-23T17:53:00.008-05:00

Nice post by Anand on Datawocky
Why the World Needs a New Database System ! The post talks about the need for a new database system built on top of commodity hardware, that can handle large amount of data, and provides an easy to use query language. On solution front, Anand's post focuses mainly on Aster Data. Although there are mainly solutions mentioned in the comments sections.

Definitely there is a need for a simple query language (SQL like) to process large amount of data distributed over commodity hardware.

I feel Hypertable , an open source version of Bigtable, may be a good way to address this problem. Hypertable uses a query language (HQL - Hypertable Query Language) that is similar to SQL. Hypertable can be installed over distributed file system like HDFS, and KFS. Since these file systems are fault-tolerant and scale well with the number of nodes in the system, Hypertable is also fault-tolerant and scalable.

I wonder how Aster data solution fares with respect to Hypertable.

$200 barrel of oil?

2008-05-07T11:54:00.002-05:00

$200 barrel of oil at the end of the year?

And check this link :
For $9995, we can make ethanol in our backyard. So cycle of waste is complete, use energy to produce crops, and use crops to produce energy/ethanol, and continue our energy hungry lifestyle ...

Freezing Austin

2007-01-17T16:59:00.000-06:00

For the first time in the last 5 years, I have seen so much ice/snow in Austin, thanks to the ice storm. Many people including me are under "house arrest" since last couple of days. It's so new to Austin that I thought of posting some pics :). Check out more pics here.

Jack is back ...

2007-01-16T16:58:00.000-06:00

Another season (6th) of "24" started with a bang. Four out of twenty-four hours are already passed with action packed sequences, and Jack, as usual, is all over the place with his self-healing power.

A trivia: if you get involved in a bar fight, and if you have an option to chose between Jack Bauer and Harry Potter for your help, then whom will you pick? Of course, Jack Bauer. See this blog for an interesting argument.

Check out this site for some interesting facts about Jack Bauer. Some of them are really funny. For example,

Jack Bauer never retreats, he just attacks in the opposite direction.
The city of Los Angeles once named a street after Jack Bauer in gratitude for his saving the city several times. They had to rename it after people kept dying when they tried to cross the street. No one crosses Jack Bauer and lives.
When Jack Bauer ran out of ammo, he caught 3 bullets in his chest and used them to reload.
Once, someone tried to tell Jack Bauer a "knock knock" joke. Jack Bauer found out who was there, who they worked for, and where the goddamned bomb was.
Jack Bauer doesn't need to eat, sleep, or use the bathroom because his organs are afraid of making him angry.
Superman is one of the few individuals who could possibly survive a confrontation with Jack Bauer. But that is only because he can fly away.
Jack Bauer once forgot where he put his keys. He then spent the next half-hour torturing himself until he gave up the location of the keys.
When Jack Bauer plays dodgeball, the ball dodges Jack Bauer.
... :)

On mood swings

2006-11-18T12:59:00.000-06:00

I was feeling a bit low in the middle of the week. After wasting a few hours, I was still not alright. In an attempt to get over it, I started asking questions like why am I feeling low? What was it that triggered the feeling? How should I cope up with this? What do others do in this situation? And I started getting some answers when I was posing the situation in the form of questions. It seems years of computer science problem solving training has deeply affected consciousness as well. Now do I need to deal with any situation by posing a relevant question? Not a bad option though :). The following blog was a good read, http://health.yahoo.com/experts/yeahdave/5837/riders-on-the-storm

I hope I can learn something from the following quotes.

"You can't expect to prevent negative feelings altogether. And you can't expect to experience positive feelings all the time...The Law of Emotional Choice directs us to acknowledge our feelings but also to refuse to get stuck in the negative ones." -- Greg Anderson

"It is common sense to take a method and try it. If it fails, admit it frankly and try another. But above all, try something." --Franklin D. Roosevelt

movie Borat

2006-11-11T15:14:00.000-06:00

I recently watched this movie Borat. While watching the movie, I was wondering what a Kazakh would think about the movie. And I was not surprised when I found that there is enough controversy about the movie that I didn't know about (check this out: Borat controversy). The movie is fictional, but I wonder how can the director/producer depict a country (and people from that country) in such a bad way, and also somewhat illogical. For example, the main character could learn driving in American highway and roads, but could not learn some basic things in the daily life.

2006-04-15T16:44:00.000-05:00

Dhoni, the official driver of Indian team :).

Theoretical Computer Science Blogs

2006-04-10T14:00:00.000-05:00

Theoretical Computer Science Blogs

Housefly with glasses

2006-04-10T13:58:00.000-05:00

Housefly Gets Glasses Made With Lasers
Can you believe this?

Algorithmic resource

2006-03-22T18:01:00.000-06:00

A useful resource: Algorithmic Links .

Kambli's bit part in Sachin's surge to stardom

2006-03-22T00:48:00.000-06:00

A touching story:
Telegraph | Sport | Kambli's bit part in Sachin's surge to stardom

Good Math, Bad Math

2006-03-17T11:36:00.000-06:00

Another math blog: Good Math, Bad Math.

PBS | I, Cringely . November 17, 2005 - Google-Mart

2005-11-20T20:53:00.000-06:00

Google building a version of

"Akamai on steroids"

Indians get hooked on to the Net

2005-11-14T18:54:00.000-06:00

35 million internet users in India, but that is still 3.5% ...

Solemn Balderdash...: Men are from Mars and Women are from…EARTH...duh!

2005-10-24T12:05:00.000-05:00

Solemn Balderdash...: Men are from Mars and Women are from…EARTH...duh! Interesting read, but somewhat one sided. Thinking of writing one from the other side with a title "Beauty with Brains" ...

Recent high-tech developments

2005-10-13T23:21:00.000-05:00

Interesting view on recent high-tech deals between M$-Yahoo, M$-Real, and Google-Sun The big picture behind Google, Microsoft, Yahoo, AOL, Real, and Sun deal-o-mania

Google formally declares war on Microsoft

2005-10-06T10:43:00.000-05:00

Another hype? "Google will launch free spreadsheet and word-processing software online"
http://www.theinquirer.net/?article=26734

Google' Word toolbar for blogging

2005-08-16T20:15:00.000-05:00

Google, one step closer to web based document writing and publishing? Check this out: Google Blogger Launches Blogger For Word Toolbar

Top 10 dot-com flops

2005-08-07T01:21:00.000-05:00

An interesting read, how VCs aka vultures spent so much money in a frenzy.

103.2 million phones in India now

2005-08-05T21:55:00.000-05:00

More mobiles than land lines,
103.2 million phones in India now

RBI readies for a 'Reddy Era'

2005-08-05T01:45:00.000-05:00

RBI readies for a 'Reddy Era' An interesting article throwing some light inside RBI.

Top Ten Aamir films - Movies

2005-08-03T23:11:00.000-05:00

Top Ten Aamir films - Movies Amir Khan, one of my favorite bollywood actor.

Yahoo! Health Expert Blogs Yoga for You - The Ripple Effect

2005-08-02T20:45:00.000-05:00

Yahoo! Health Expert Blogs Yoga for You - The Ripple Effect Evergreen useful tips "respect for others, respect for themselves, respect for the environment, general manners, staying healthy, a little yoga, and an open mind."

PhD's who are A.B.D. (all but dissertation)

2005-07-29T19:30:00.000-05:00

Thursday, July 28, 2005

Frodo Baggins, A.B.D.

By SUSIE J. LEE

When I was A.B.D., I tried to motivate myself to write my dissertation by

setting deadlines that corresponded with the premieres of Peter Jackson's

cinematic interpretation of J.R.R. Tolkien's epic trilogy, The Lord of the

Rings. My goal was to have a first full draft of the dissertation written

by the time the third movie, The Return of the King, came out at the end

of 2003, and to watch all three films back-to-back in Times Square in

celebration of the achievement.

I didn't exactly meet that deadline. But once I had finished my

dissertation and successfully graduated, I watched all three movies again,

this time on DVD, and was struck by how closely the story mirrors the

experience of writing a dissertation.

For those who have not read the books or seen the films, the significant

parts of the story center around a long journey made by a hobbit named

Frodo Baggins. He travels across a land called Middle-earth to throw a

ring into the middle of a volcano called Mount Doom -- an action that, for

doctoral students, is known as "filing the dissertation."

Like many a dissertator, Frodo's terrible and treacherous mission has a

dual nature. He cannot, and does not, accomplish the goal without the help

of others, but ultimately, he must bear the great load alone.

Frodo is accompanied on the journey by his hobbit friends Sam, Merry, and

Pippin. Merry and Pippin are like fellow graduate students still doing

their course work. Their carefree nature disappears along the journey,

however, as they begin to recognize the impending doom of becoming All But

Dissertation. By the end of the second movie, The Two Towers, Merry and

Pippin have passed their comprehensive exams and gained a greater

maturity, but it is not clear whether they will go on to the dissertation

phase. Maybe they've decided that an academic career is not for them.

Frodo, on the other hand, has made the decision that he wants to go all

the way. His most important companion is Sam, who is the equivalent of

Frodo's "partner."

Sam is not a Ph.D. student, and more than anyone else, he has the terrible

burden of being the one closest to the ring bearer. Sam's own fate is tied

to that of the ring yet he is helpless to determine his future in a direct

manner. He cannot make Frodo finish; he can only try to make it easier for

Frodo to do so. He is the long-suffering hero whom every ring bearer

thanks at the beginning or end of the acknowledgments of the dissertation

-- the one about whom everyone writes "I couldn't have done it without

you."

On their way to file the dissertation, Sam and Frodo separate one time.

The separation is the result of a deception spun by a fallen soul named

Gollum -- aka, the doctoral candidate who will never finish.

Gollum lived with the ring for many years and it destroyed his life, mind,

and well-being. Gollum is the living image of what Frodo will become if

Frodo cannot complete his task. Frodo in fact pities Gollum, while Sam can

only feel disgust and distrust for the miserable creature.

If the ring is to be destroyed -- and the dissertation finished -- new

alliances must be formed. Without that fellowship, Frodo's quest is

doomed. But a partner alone cannot provide enough support for the

difficult mission.

For example, he is stabbed three times during the course of his journey by

disgusting and horrible creatures. He is hounded by terrifying beings

called the Ringwraiths. Those attacks are the equivalent of the

dissertator's endless financial struggles. Each loss of funds prevents him

from paying enormous photocopying costs, expenses for travel to archives,

bills for books and supplies, health insurance, and campus fees. They take

a toll on his morale and his health and increase his stress and

exhaustion.

One of Frodo's key supporters who tries to protect him from those problems

is a wizard named Gandalf, who, for our purposes, represents Frodo's

dissertation committee, usually made up of three people.

Gandalf is instrumental in running interference for Frodo and making sure

that he can complete his mission. He writes recommendations for grants and

letters of introduction to libraries. He critiques drafts, locates

possible sources of money, and feeds his student whenever possible. Most

important, he offers intellectual guidance and moral support. Gandalf has

his own challenges, however. In the Mines of Moria, he faces down a

horrifying demon called the Balrog -- meaning he must also teach,

research, publish, and serve on committees.

Frodo's "fellowship" also includes family, friends, dissertation groups,

fellow doctoral students, professors, undergraduates, and archival and

administrative staff members. They provide counsel, writing deadlines,

good company, book references, housing, theoretical critiques, and other

key assistance. There are even filmmakers like Peter Jackson who provide

incentives around which dissertation deadlines can be set.

Yet while all that support is critical, the mission of the ring is still

Frodo's alone. Even with help, can he achieve his goal?

The drama of filing the dissertation is heightened at the end of the

process, in those last months of writing, editing, and formatting. A

critical scene in The Return of the King highlights the deep emotional

struggle between Frodo and his alter ego, Gollum.

Frodo and Sam have finally arrived at Mount Doom, which means that Frodo

finally has the full draft. But he looks terrible; he has been defeated

emotionally and spiritually by the burden of carrying the ring. He has

reached the end of his long journey, but will he file?

At the volcano, Sam yells to Frodo to throw in the ring. But by this time,

the strain and burden of carrying the ring for so long has damaged Frodo's

mind; he doesn't want to let go. He looks at Sam with a crazed look and

says, "The ring is mine!" which, translated, means that he can't or won't

finish; he has more research to do, more editing; the dissertation is just

not good enough; he must reformat the page numbers.

He has taken the step toward becoming Gollum. He will remain A.B.D.

forever. Sam cries pitifully. His life is ruined, too.

All of a sudden, Gollum appears and wrestles Frodo to the ground. They

struggle for the ring and Gollum bites off Frodo's finger. Gollum has

unwittingly forced Frodo to rise up and save himself from himself. As they

struggle, they fall from the ledge, and the ring falls into the molten

lava (along with Gollum). The deed is finally done. The dissertation is

filed.

But Frodo has completed his mission unwillingly. The year of carrying the

ring has damaged him and taken the joy from his life. He has completed his

quest, but he's not happy. Can he recover?

Several years later, Frodo is back in his comfortable home in the Shire

and has completed the book manuscript for the story of his journey, called

The Lord of the Rings. But he confesses to Sam that he is still not at

peace. He leaves the Shire on a big boat to find peace and be with his

mentor, Gandalf, and other associate and full professors in a faraway land

called tenure.

Having shared my Frodo allegory with my dissertation group and my fellow

graduate students, we've started to refer to the dissertation as the

"ring." When we share stories about writing 12 hours a day for months on

end with little human contact, or about feeling angry with people who have

the time to eat in nice restaurants and go to the movies, we say, "That's

the power of the ring."

The moral of the story, because there is always a moral to these kinds of

stories, is to take care of your health and appreciate those around you.

Unlike Frodo, we all have the job market to go through, too.

Susie J. Lee received her Ph.D. in history from Cornell University in

August 2004.

PJ: Santa series

2005-07-28T18:37:00.000-05:00

Once a sardar was looking at a WANTED poster & was wondering -

Saala wanted tha to photo kheenchne ke baad use jaane kyon diya ?

*************

Sardar car ki battery change karwane gaya ...

Mechanic - Sahab, Exide ki daal doon ?

Sardar - Nahin yaar, dono side ki daal de, warna phir problem hogi.

*************

A sardar on an interview for the post of detective was asked a question
-

Interviewer - Who killed Gandhiji ?

Sardar - Thanks for giving me the job, I will investigate.

*************

Sardar returns book to library, bangs it on table & says - What a shit ?
"I

read the whole book, too many character, no story at all" ?.

Librarian : So, you are the one who took the Telephone Directory....

*************

2 Days of Powercut in India made life miserable. Worst affected was Amritsar

where all the SARDARS were stuck for 48 hrs. on Escalaters.....

*************

Two Sardars are driving a Car, one puts on the indicator and asks the other

to check whether it is working.

He puts his head out and says - YES..NO..YES..NO..YES..NO

*************

Sardarji, tell me ...., what is the meaning of SMS ?

Sardar angrily said, i know -

it means....

S - Sardaron ke

M - Mazak udane ki

S - Service

*************

Banta : Oye to har SMS ko do baar kyom bhej raha hai ?

Santa : Kyunki tujhe agar ek forward karna ho to dusra tere paas rahe !!!

PJ: Santa goes for an accouting test

2005-07-28T18:36:00.000-05:00

Santa wanted to be an accountant, so he went for an aptitude test:

Tester: If I give you two Rabbits, and two rabbits, and another two rabbits, how many rabbits have you got?

Santa : SEVEN!

Tester : No, listen carefully again. If I give you two Rabbits, and two rabbits, and another two rabbits, how many rabbits have you got?

Santa : SEVEN!

Tester : Let's try this another way. If I give you two bottles of beer, and two bottles of beer, and another two bottles of beer, how many bottles of beer have you got?

Santa : SIX.

Tester : Good! Now, if I give you two Rabbits, and two rabbits, and another two rabbits, how many rabbits have you got?

Santa : SEVEN!

Tester : How on Earth do you work out that three lots of two rabbits is seven?

Santa : I've already got one rabbit at home.

Tester : #@$%@^#&$&*#$*#($((((!!!!!!!!!!

India-vs-China in the new world

2005-05-21T12:25:00.000-05:00

Why everybody is trying to compare India and China, and trying to predict one is going to do better than the other?

An article about research institutes in India

2005-03-27T03:41:00.000-06:00

Interesting to read : How to be a good CEO, Raghnath Anant Mashelkar,
http://us.rediff.com/money/2005/mar/24spec.htm